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Sample records for vector autoregressive var

  1. A Vector AutoRegressive (VAR) Approach to the Credit Channel for ...

    African Journals Online (AJOL)

    This paper is an attempt to determine the presence and empirical significance of monetary policy and the bank lending view of the credit channel for Mauritius, which is particularly relevant at these times. A vector autoregressive (VAR) model of order three is used to examine the monetary transmission mechanism using ...

  2. METODE VECTOR AUTOREGRESSIVE (VAR DALAM PERAMALAN JUMLAH WISATAWAN MANCANEGARA KE BALI

    Directory of Open Access Journals (Sweden)

    TJOK GDE SAHITYAHUTTI RANANGGA

    2018-05-01

    Full Text Available The purposes of this research were to model and to forecast the number of foreign tourists (Australia, China, and Japan arrival to Bali using vector autoregressive (VAR method. The estimated of VAR model obtained to forecast the number of foreign tourists to Bali is the sixth order VAR (VAR(6.We used multivariate least square method to estimate the VAR(6’s parameters.The mean absolute percentage error (MAPE in this model were as follows 6.8% in predicting the number of Australian tourists, 15.9% in predicting the number of Chinese tourists, and 9% in predicting the number of Japanese tourists. The prediction of Australian, Chinese, and Japanese tourists arrival to Bali for July 2017 to December 2017 tended  to experience up and downs that were not too high compared to the previous months.

  3. iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

    Science.gov (United States)

    Liu, Siwei; Molenaar, Peter C M

    2014-12-01

    This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

  4. Noncausal Bayesian Vector Autoregression

    DEFF Research Database (Denmark)

    Lanne, Markku; Luoto, Jani

    We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...

  5. Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price

    Science.gov (United States)

    Suharsono, Agus; Aziza, Auliya; Pramesti, Wara

    2017-12-01

    Capital markets can be an indicator of the development of a country's economy. The presence of capital markets also encourages investors to trade; therefore investors need information and knowledge of which shares are better. One way of making decisions for short-term investments is the need for modeling to forecast stock prices in the period to come. Issue of stock market-stock integration ASEAN is very important. The problem is that ASEAN does not have much time to implement one market in the economy, so it would be very interesting if there is evidence whether the capital market in the ASEAN region, especially the countries of Indonesia, Malaysia, Philippines, Singapore and Thailand deserve to be integrated or still segmented. Furthermore, it should also be known and proven What kind of integration is happening: what A capital market affects only the market Other capital, or a capital market only Influenced by other capital markets, or a Capital market as well as affecting as well Influenced by other capital markets in one ASEAN region. In this study, it will compare forecasting of Indonesian share price (IHSG) with neighboring countries (ASEAN) including developed and developing countries such as Malaysia (KLSE), Singapore (SGE), Thailand (SETI), Philippines (PSE) to find out which stock country the most superior and influential. These countries are the founders of ASEAN and share price index owners who have close relations with Indonesia in terms of trade, especially exports and imports. Stock price modeling in this research is using multivariate time series analysis that is VAR (Vector Autoregressive) and VECM (Vector Error Correction Modeling). VAR and VECM models not only predict more than one variable but also can see the interrelations between variables with each other. If the assumption of white noise is not met in the VAR modeling, then the cause can be assumed that there is an outlier. With this modeling will be able to know the pattern of relationship

  6. Use of (Time-Domain) Vector Autoregressions to Test Uncovered Interest Parity

    OpenAIRE

    Takatoshi Ito

    1984-01-01

    In this paper, a vector autoregression model (VAR) is proposed in order to test uncovered interest parity (UIP) in the foreign exchange market. Consider a VAR system of the spot exchange rate (yen/dollar), the domestic (US) interest rate and the foreign (Japanese) interest rate, describing the interdependence of the domestic and international financia lmarkets. Uncovered interest parity is stated as a null hypothesis that the current difference between the two interest rates is equal to the d...

  7. MACROECONOMIC FORECASTING USING BAYESIAN VECTOR AUTOREGRESSIVE APPROACH

    Directory of Open Access Journals (Sweden)

    D. Tutberidze

    2017-04-01

    Full Text Available There are many arguments that can be advanced to support the forecasting activities of business entities. The underlying argument in favor of forecasting is that managerial decisions are significantly dependent on proper evaluation of future trends as market conditions are constantly changing and require a detailed analysis of future dynamics. The article discusses the importance of using reasonable macro-econometric tool by suggesting the idea of conditional forecasting through a Vector Autoregressive (VAR modeling framework. Under this framework, a macroeconomic model for Georgian economy is constructed with the few variables believed to be shaping business environment. Based on the model, forecasts of macroeconomic variables are produced, and three types of scenarios are analyzed - a baseline and two alternative ones. The results of the study provide confirmatory evidence that suggested methodology is adequately addressing the research phenomenon and can be used widely by business entities in responding their strategic and operational planning challenges. Given this set-up, it is shown empirically that Bayesian Vector Autoregressive approach provides reasonable forecasts for the variables of interest.

  8. Model reduction methods for vector autoregressive processes

    CERN Document Server

    Brüggemann, Ralf

    2004-01-01

    1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims' (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of 'too many incredible restrictions' based on 'supposed a priori knowledge' in large scale macroeconometric models which were popular at that time. Therefore, he advo­ cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to characterize the underlying dynamics in systems of time series. In particular, tools to summarize the dynamic interaction between the system variables, such as impulse response analysis or forecast error variance decompo­ sitions, have been developed over the years. The econometrics of VAR models and related quantities i...

  9. Exchange rate pass-through in Switzerland: Evidence from vector autoregressions

    OpenAIRE

    Jonas Stulz

    2007-01-01

    This study investigates the pass-through of exchange rate and import price shocks to different aggregated prices in Switzerland. The baseline analysis is carried out with recursively identified vector autoregressive (VAR) models. The data set comprises monthly observations, and pass-through effects are quantified by means of impulse response functions. Evidence shows that the exchange rate pass-through to import prices is substantial (although incomplete), but only moderate to total consumer ...

  10. Vector autoregressive model approach for forecasting outflow cash in Central Java

    Science.gov (United States)

    hoyyi, Abdul; Tarno; Maruddani, Di Asih I.; Rahmawati, Rita

    2018-05-01

    Multivariate time series model is more applied in economic and business problems as well as in other fields. Applications in economic problems one of them is the forecasting of outflow cash. This problem can be viewed globally in the sense that there is no spatial effect between regions, so the model used is the Vector Autoregressive (VAR) model. The data used in this research is data on the money supply in Bank Indonesia Semarang, Solo, Purwokerto and Tegal. The model used in this research is VAR (1), VAR (2) and VAR (3) models. Ordinary Least Square (OLS) is used to estimate parameters. The best model selection criteria use the smallest Akaike Information Criterion (AIC). The result of data analysis shows that the AIC value of VAR (1) model is equal to 42.72292, VAR (2) equals 42.69119 and VAR (3) equals 42.87662. The difference in AIC values is not significant. Based on the smallest AIC value criteria, the best model is the VAR (2) model. This model has satisfied the white noise assumption.

  11. Numerical limitations in application of vector autoregressive modeling and Granger causality to analysis of EEG time series

    Science.gov (United States)

    Kammerdiner, Alla; Xanthopoulos, Petros; Pardalos, Panos M.

    2007-11-01

    In this chapter a potential problem with application of the Granger-causality based on the simple vector autoregressive (VAR) modeling to EEG data is investigated. Although some initial studies tested whether the data support the stationarity assumption of VAR, the stability of the estimated model is rarely (if ever) been verified. In fact, in cases when the stability condition is violated the process may exhibit a random walk like behavior or even be explosive. The problem is illustrated by an example.

  12. A Dynamic Model of U.S. Sugar-Related Markets: A Cointegrated Vector Autoregression Approach

    OpenAIRE

    Babula, Ronald A.; Newman, Douglas; Rogowsky, Robert A.

    2006-01-01

    The methods of the cointegrated vector autoregression (VAR) model are applied to monthly U.S. markets for sugar and for sugar-using markets for confectionary, soft drink, and bakery products. Primarily a methods paper, we apply Johansen and Juselius' advanced procedures to these markets for perhaps the first time, with focus on achievement of a statistically adequate model through analysis of a battery of advanced statistical diagnostic tests and on exploitation of the system's cointegration ...

  13. Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

    International Nuclear Information System (INIS)

    Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

    2017-01-01

    This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

  14. Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)

    2017-01-15

    This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

  15. Likelihood inference for a fractionally cointegrated vector autoregressive model

    DEFF Research Database (Denmark)

    Johansen, Søren; Ørregård Nielsen, Morten

    2012-01-01

    such that the process X_{t} is fractional of order d and cofractional of order d-b; that is, there exist vectors ß for which ß'X_{t} is fractional of order d-b, and no other fractionality order is possible. We define the statistical model by 0inference when the true values satisfy b0¿1/2 and d0-b0......We consider model based inference in a fractionally cointegrated (or cofractional) vector autoregressive model with a restricted constant term, ¿, based on the Gaussian likelihood conditional on initial values. The model nests the I(d) VAR model. We give conditions on the parameters...... process in the parameters when errors are i.i.d. with suitable moment conditions and initial values are bounded. When the limit is deterministic this implies uniform convergence in probability of the conditional likelihood function. If the true value b0>1/2, we prove that the limit distribution of (ß...

  16. Debt Contagion in Europe: A Panel-Vector Autoregressive (VAR Analysis

    Directory of Open Access Journals (Sweden)

    Florence Bouvet

    2013-12-01

    Full Text Available The European sovereign-debt crisis began in Greece when the government announced in December, 2009, that its debt reached 121% of GDP (or 300 billion euros and its 2009 budget deficit was 12.7% of GDP, four times the level allowed by the Maastricht Treaty. The Greek crisis soon spread to other Economic and Monetary Union (EMU countries, notably Ireland, Portugal, Spain and Italy. Using quarterly data for the 2000–2011 period, we implement a panel-vector autoregressive (PVAR model for 11 EMU countries to examine the extent to which a rise in a country’s bond-yield spread or debt-to-GDP ratio affects another EMU countries’ fiscal and macroeconomic outcomes. To distinguish between interdependence and contagion among EMU countries, we compare results obtained for the pre-crisis period (2000–2007 with the crisis period (2008–2011 and control for global risk aversion.

  17. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

    Science.gov (United States)

    Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

    2018-01-01

    Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

  18. Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

    Science.gov (United States)

    Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

    2017-01-01

    This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

    Science.gov (United States)

    Beltz, Adriene M; Molenaar, Peter C M

    2016-01-01

    Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

  20. Estimation of pure autoregressive vector models for revenue series ...

    African Journals Online (AJOL)

    This paper aims at applying multivariate approach to Box and Jenkins univariate time series modeling to three vector series. General Autoregressive Vector Models with time varying coefficients are estimated. The first vector is a response vector, while others are predictor vectors. By matrix expansion each vector, whether ...

  1. The impact of oil-price shocks on Hawaii's economy: A case study using vector autoregression

    International Nuclear Information System (INIS)

    Gopalakrishnan, C.; Tian, X.; Tran, D.

    1991-01-01

    The effects of oil-price shocks on the macroeconomic performance of a non-oil-producing, oil-importing state are studied in terms of Hawaii's experience (1974-1986) using Vector Autoregression (VAR). The VAR model contains three macrovariables-real oil price, interest rate, and real GNP, and three regional variable-total civilian labor force, Honolulu consumer price index, and real personal income. The results suggested that oil-price shock had a positive effect on interest rate as well as local price (i.e., higher interest and higher local price), but a negative influence on real GNP. The negative income effect, however, was offset by the positive employment effect. The price of oil was found to be exogenous to all other variables in the system. The macrovariables exerted a pronounced impact on Hawaii's economy, most notably on consumer price

  2. Some tests for parameter constancy in cointegrated VAR-models

    DEFF Research Database (Denmark)

    Hansen, Henrik; Johansen, Søren

    1999-01-01

    Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

  3. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA; GENTON, MARC G.

    2009-01-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided

  4. Bayesian model averaging in vector autoregressive processes with an investigation of stability of the US great ratios and risk of a liquidity trap in the USA, UK and Japan

    NARCIS (Netherlands)

    R.W. Strachan (Rodney); H.K. van Dijk (Herman)

    2007-01-01

    textabstractA Bayesian model averaging procedure is presented within the class of vector autoregressive (VAR) processes and applied to two empirical issues. First, stability of the "Great Ratios" in U.S. macro-economic time series is investigated, together with the presence and e¤ects of permanent

  5. Computing level-impulse responses of log-specified VAR systems

    NARCIS (Netherlands)

    Wieringa, J.E.; Horvath, C.

    2005-01-01

    Impulse response functions (IRFs) are often used to analyze the dynamic behavior of a vector autoregressive (VAR) system. In many applications of VAR modelling, the variables are log-transformed before the model is estimated. If this is the case, the results of the IRFs do not have a direct

  6. Price transmission for agricultural commodities in Uganda: An empirical vector autoregressive analysis

    DEFF Research Database (Denmark)

    Lassen Kaspersen, Line; Føyn, Tullik Helene Ystanes

    This paper investigates price transmission for agricultural commodities between world markets and the Ugandan market in an attempt to determine the impact of world market prices on the Ugandan market. Based on the realization that price formation is not a static concept, a dynamic vector...... price relations, i.e. the price variations between geographically separated markets in Uganda and the world markets. Our analysis indicates that food markets in Uganda, based on our study of sorghum price transmission, are not integrated into world markets, and that oil prices are a very determining...... autoregressive (VAR) model is presented. The prices of Robusta coffee and sorghum are examined, as both of these crops are important for the domestic economy of Uganda – Robusta as a cash crop, mainly traded internationally, and sorghum for consumption at household level. The analysis focuses on the spatial...

  7. Oracle Inequalities for High Dimensional Vector Autoregressions

    DEFF Research Database (Denmark)

    Callot, Laurent; Kock, Anders Bredahl

    This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO in stationary vector autoregressive models. These inequalities are used to establish consistency of the LASSO even when the number of parameters is of a much larger order...

  8. Optimal Hedging with the Vector Autoregressive Model

    NARCIS (Netherlands)

    L. Gatarek (Lukasz); S.G. Johansen (Soren)

    2014-01-01

    markdownabstract__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be

  9. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA

    2009-09-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided for stationarity of such models. We also study estimation of the proposed model using P-splines, hypothesis testing, asymptotics, selection of the order of the autoregression and of the smoothing parameters and nonlinear forecasting. We perform simulation experiments to evaluate our model in various settings. We illustrate our methodology on a climate data set and show that our model provides more accurate yearly forecasts of the El Niño phenomenon, the unusual warming of water in the Pacific Ocean. © 2009 Board of the Foundation of the Scandinavian Journal of Statistics.

  10. The Integration Order of Vector Autoregressive Processes

    DEFF Research Database (Denmark)

    Franchi, Massimo

    We show that the order of integration of a vector autoregressive process is equal to the difference between the multiplicity of the unit root in the characteristic equation and the multiplicity of the unit root in the adjoint matrix polynomial. The equivalence with the standard I(1) and I(2...

  11. vector bilinear autoregressive time series model and its superiority

    African Journals Online (AJOL)

    KEYWORDS: Linear time series, Autoregressive process, Autocorrelation function, Partial autocorrelation function,. Vector time .... important result on matrix algebra with respect to the spectral ..... application to covariance analysis of super-.

  12. Vector bilinear autoregressive time series model and its superiority ...

    African Journals Online (AJOL)

    In this research, a vector bilinear autoregressive time series model was proposed and used to model three revenue series (X1, X2, X3) . The “orders” of the three series were identified on the basis of the distribution of autocorrelation and partial autocorrelation functions and were used to construct the vector bilinear models.

  13. A VAR Analysis Regarding Tax Evasion and Tax Pressure in Romania

    Directory of Open Access Journals (Sweden)

    Boștină Florin

    2017-01-01

    The main aim of the paper is to identify the relationship that exists between tax evasion and tax pressure in Romania, between 2000 and 2013, using an autoregressive vector type of analysis. The VAR model with 3 lags can be considered as representative in order to describe autoregressive links between tax evasion and fiscal pressure in Romania.

  14. Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

    Science.gov (United States)

    Aydin, Alev Dilek; Caliskan Cavdar, Seyma

    2015-01-01

    The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method.

  15. Optimal hedging with the cointegrated vector autoregressive model

    DEFF Research Database (Denmark)

    Gatarek, Lukasz; Johansen, Søren

    We derive the optimal hedging ratios for a portfolio of assets driven by a Coin- tegrated Vector Autoregressive model (CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the...

  16. Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting

    Directory of Open Access Journals (Sweden)

    Alev Dilek Aydin

    2015-01-01

    Full Text Available The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method.

  17. A General Representation Theorem for Integrated Vector Autoregressive Processes

    DEFF Research Database (Denmark)

    Franchi, Massimo

    We study the algebraic structure of an I(d) vector autoregressive process, where d is restricted to be an integer. This is useful to characterize its polynomial cointegrating relations and its moving average representation, that is to prove a version of the Granger representation theorem valid...

  18. On the detection of effective marketing instruments and causality in VAR models

    NARCIS (Netherlands)

    Horváth, C.; Otter, P.W.

    2000-01-01

    Dynamic multivariate models become more and more popular in analyzing the behavior of competive marketing environments. Takada and Bass (1998), Dekimpe, Hanssens and Silva-Rosso (1999), and Dekimpe and Hanssens (1999) recommend to use Vector Autoregressive (VAR) models because they provide

  19. Bridging Economic Theory Models and the Cointegrated Vector Autoregressive Model

    DEFF Research Database (Denmark)

    Møller, Niels Framroze

    2008-01-01

    Examples of simple economic theory models are analyzed as restrictions on the Cointegrated VAR (CVAR). This establishes a correspondence between basic economic concepts and the econometric concepts of the CVAR: The economic relations correspond to cointegrating vectors and exogeneity in the econo......Examples of simple economic theory models are analyzed as restrictions on the Cointegrated VAR (CVAR). This establishes a correspondence between basic economic concepts and the econometric concepts of the CVAR: The economic relations correspond to cointegrating vectors and exogeneity...... are related to expectations formation, market clearing, nominal rigidities, etc. Finally, the general-partial equilibrium distinction is analyzed....

  20. Vector Autoregressive (VAR) Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example

    Science.gov (United States)

    Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M.

    2016-01-01

    Background Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display inter-related vital sign changes during situations of physiologic stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. Purpose The purpose of this article is to illustrate development of patient-specific VAR models using vital sign time series (VSTS) data in a sample of acutely ill, monitored, step-down unit (SDU) patients, and determine their Granger causal dynamics prior to onset of an incident CRI. Approach CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40–140/minute, RR = 8–36/minute, SpO2 < 85%) and persisting for 3 minutes within a 5-minute moving window (60% of the duration of the window). A 6-hour time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity; (b) appropriate lag was determined using a lag-length selection criteria; (c) the VAR model was constructed; (d) residual autocorrelation was assessed with the Lagrange Multiplier test; (e) stability of the VAR system was checked; and (f) Granger causality was evaluated in the final stable model. Results The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%) (i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing

  1. Circular Conditional Autoregressive Modeling of Vector Fields.

    Science.gov (United States)

    Modlin, Danny; Fuentes, Montse; Reich, Brian

    2012-02-01

    As hurricanes approach landfall, there are several hazards for which coastal populations must be prepared. Damaging winds, torrential rains, and tornadoes play havoc with both the coast and inland areas; but, the biggest seaside menace to life and property is the storm surge. Wind fields are used as the primary forcing for the numerical forecasts of the coastal ocean response to hurricane force winds, such as the height of the storm surge and the degree of coastal flooding. Unfortunately, developments in deterministic modeling of these forcings have been hindered by computational expenses. In this paper, we present a multivariate spatial model for vector fields, that we apply to hurricane winds. We parameterize the wind vector at each site in polar coordinates and specify a circular conditional autoregressive (CCAR) model for the vector direction, and a spatial CAR model for speed. We apply our framework for vector fields to hurricane surface wind fields for Hurricane Floyd of 1999 and compare our CCAR model to prior methods that decompose wind speed and direction into its N-S and W-E cardinal components.

  2. Bridging Economic Theory Models and the Cointegrated Vector Autoregressive Model

    DEFF Research Database (Denmark)

    Møller, Niels Framroze

    2008-01-01

    Examples of simple economic theory models are analyzed as restrictions on the Cointegrated VAR (CVAR). This establishes a correspondence between basic economic concepts and the econometric concepts of the CVAR: The economic relations correspond to cointegrating vectors and exogeneity in the econo......Examples of simple economic theory models are analyzed as restrictions on the Cointegrated VAR (CVAR). This establishes a correspondence between basic economic concepts and the econometric concepts of the CVAR: The economic relations correspond to cointegrating vectors and exogeneity...... parameters of the CVAR are shown to be interpretable in terms of expectations formation, market clearing, nominal rigidities, etc. The general-partial equilibrium distinction is also discussed....

  3. Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility

    DEFF Research Database (Denmark)

    Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

    Many key macro-economic and financial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...

  4. Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, A. M. Robert

    Many key macro-economic and …nancial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...

  5. Testing exact rational expectations in cointegrated vector autoregressive models

    DEFF Research Database (Denmark)

    Johansen, Søren; Swensen, Anders Rygh

    1999-01-01

    This paper considers the testing of restrictions implied by rational expectations hypotheses in a cointegrated vector autoregressive model for I(1) variables. If the rational expectations involve one-step-ahead observations only and the coefficients are known, an explicit parameterization...... of the restrictions is found, and the maximum-likelihood estimator is derived by regression and reduced rank regression. An application is given to a present value model....

  6. Temporal aggregation in first order cointegrated vector autoregressive

    DEFF Research Database (Denmark)

    la Cour, Lisbeth Funding; Milhøj, Anders

    2006-01-01

    We study aggregation - or sample frequencies - of time series, e.g. aggregation from weekly to monthly or quarterly time series. Aggregation usually gives shorter time series but spurious phenomena, in e.g. daily observations, can on the other hand be avoided. An important issue is the effect of ...... of aggregation on the adjustment coefficient in cointegrated systems. We study only first order vector autoregressive processes for n dimensional time series Xt, and we illustrate the theory by a two dimensional and a four dimensional model for prices of various grades of gasoline....

  7. Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Kapetanios, George

    We address the issue of modelling and forecasting macroeconomic variables using rich datasets, by adopting the class of Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares (...

  8. EFFECTS OF MONETARY POLICY IN ROMANIA - A VAR APPROACH

    Directory of Open Access Journals (Sweden)

    Iulian Popescu

    2012-10-01

    Full Text Available Understanding how monetary policy decisions affect inflation and other economic variables is particularly important. In this paper we consider the implications of monetary policy under the inflation targeting regime in Romania, based on an autoregressive vector method including recursive VAR and structural VAR (SVAR. Therefore, we focus on assessing the extent and persistence of monetary policy effects on gross domestic product (GDP, price level, extended monetary aggregate (M3 and exchange rate. The main results of VAR analysis reflect a negative response of consumer price index (CPI, GDP and M3 and positive nominal exchange rate behaviour to a monetary policy shock, and also a limited impact of a short-term interest rate shock in explaining the consumer prices, production and exchange rate fluctuations.

  9. VAR IPP-IPC Model Simulation

    Directory of Open Access Journals (Sweden)

    Juan P. Pérez Monsalve

    2014-12-01

    Full Text Available This work analyzed the relationship of the two main Price indicators in the Colombian economy, the IPP and the IPC. For this purpose, we identified the theory comprising both indexes to then develop a vector autoregressive model, which shows the reaction to shocks both in itself as in the other variable, whose impact continues propagating in the long term. Additionally, the work presents a simulation of the VAR model through the Monte Carlo method, verifying the coincidence in distributions of probability and volatility levels, as well as the existence correlation over time

  10. Bias-correction in vector autoregressive models

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard

    2014-01-01

    We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...

  11. Temporal aggregation in first order cointegrated vector autoregressive models

    DEFF Research Database (Denmark)

    La Cour, Lisbeth Funding; Milhøj, Anders

    We study aggregation - or sample frequencies - of time series, e.g. aggregation from weekly to monthly or quarterly time series. Aggregation usually gives shorter time series but spurious phenomena, in e.g. daily observations, can on the other hand be avoided. An important issue is the effect of ...... of aggregation on the adjustment coefficient in cointegrated systems. We study only first order vector autoregressive processes for n dimensional time series Xt, and we illustrate the theory by a two dimensional and a four dimensional model for prices of various grades of gasoline...

  12. Empirical Vector Autoregressive Modeling

    NARCIS (Netherlands)

    M. Ooms (Marius)

    1993-01-01

    textabstractChapter 2 introduces the baseline version of the VAR model, with its basic statistical assumptions that we examine in the sequel. We first check whether the variables in the VAR can be transformed to meet these assumptions. We analyze the univariate characteristics of the series.

  13. A representation theory for a class of vector autoregressive models for fractional processes

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    Based on an idea of Granger (1986), we analyze a new vector autoregressive model defined from the fractional lag operator 1-(1-L)^{d}. We first derive conditions in terms of the coefficients for the model to generate processes which are fractional of order zero. We then show that if there is a un...... root, the model generates a fractional process X(t) of order d, d>0, for which there are vectors ß so that ß'X(t) is fractional of order d-b, 0...

  14. Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach

    International Nuclear Information System (INIS)

    Xu, Bin; Lin, Boqiang

    2015-01-01

    Energy saving and carbon dioxide emission reduction in China is attracting increasing attention worldwide. At present, China is in the phase of rapid urbanization and industrialization, which is characterized by rapid growth of energy consumption. China's transport sector is highly energy-consuming and pollution-intensive. Between 1980 and 2012, the carbon dioxide emissions in China's transport sector increased approximately 9.7 times, with an average annual growth rate of 7.4%. Identifying the driving forces of the increase in carbon dioxide emissions in the transport sector is vital to developing effective environmental policies. This study uses Vector Autoregressive model to analyze the influencing factors of the changes in carbon dioxide emissions in the sector. The results show that energy efficiency plays a dominant role in reducing carbon dioxide emissions. Private vehicles have more impact on emission reduction than cargo turnover due to the surge in private car population and its low energy efficiency. Urbanization also has significant effect on carbon dioxide emissions because of large-scale population movements and the transformation of the industrial structure. These findings are important for the relevant authorities in China in developing appropriate energy policy and planning for the transport sector. - Highlights: • The driving forces of CO 2 emissions in China's transport sector were investigated. • Energy efficiency plays a dominant role in reducing carbon dioxide emissions. • Urbanization has significant effect on CO 2 emissions due to large-scale migration. • The role of private cars in reducing emissions is more important than cargo turnover

  15. Bias-correction in vector autoregressive models: A simulation study

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard

    We analyze and compare the properties of various methods for bias-correcting parameter estimates in vector autoregressions. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that this simple...... and easy-to-use analytical bias formula compares very favorably to the more standard but also more computer intensive bootstrap bias-correction method, both in terms of bias and mean squared error. Both methods yield a notable improvement over both OLS and a recently proposed WLS estimator. We also...... of pushing an otherwise stationary model into the non-stationary region of the parameter space during the process of correcting for bias....

  16. PENERAPAN MODEL ARBITRAGE PRICING THEORY DENGAN PENDEKATAN VECTOR AUTOREGRESSION DALAM MENGESTIMASI EXPECTED RETURN SAHAM (Studi Kasus: Saham-Saham Kompas100 Periode 2010-2013

    Directory of Open Access Journals (Sweden)

    VIAN RISKA AYUNING TYAS

    2014-01-01

    Full Text Available The Arbitrage Pricing Theory (APT is an alternative model to estimate the price of securities based of arbitrage concept. In APT, the returns of securities are affected by several factors. This research is aimed to estimate the expected returns of securities using APT model and Vector Autoregressive model. There are ten stocks incorporated in Kompas100 index and four macroeconomic variables, these are inflation, exchange rates, the amountof circulate money (JUB, and theinterest rateof Bank Indonesia(SBI are applied in this research. The first step in using VAR is to test the stationary of the data using colerogram and the results indicate that all data are stationary. The second step is to select the optimal lag based on the smallest value of AIC. The Granger causality test shows that the LPKR stock is affected by the inflation and the exchange rate while the nine other stocks do not show the existence of the expected causality. The results of causality test are then estimated by the VAR models in order to obtain expected returnof macroeconomic factors. The expected return of macroeconomic factors obtained is used in the APT model, then the expected return stock LPKR is calculated. It shows that the expected return of LPKR is 3,340%

  17. PENERAPAN MODEL ARBITRAGE PRICING THEORY DENGAN PENDEKATAN VECTOR AUTOREGRESSION DALAM MENGESTIMASI EXPECTED RETURN SAHAM (Studi Kasus: Saham-Saham Kompas100 Periode 2010-2013

    Directory of Open Access Journals (Sweden)

    VIAN RISKA AYUNING TYAS

    2014-08-01

    Full Text Available The Arbitrage Pricing Theory (APT is an alternative model to estimate the price of securities based of arbitrage concept. In APT, the returns of securities are affected by several factors. This research is aimed to estimate the expected returns of securities using APT model and Vector Autoregressive model. There are ten stocks incorporated in Kompas100 index and four macroeconomic variables, these are inflation, exchange rates, the amountof circulate money (JUB, and theinterest rateof Bank Indonesia(SBI are applied in this research. The first step in using VAR is to test the stationary of the data using colerogram and the results indicate that all data are stationary. The second step is to select the optimal lag based on the smallest value of AIC. The Granger causality test shows that the LPKR stock is affected by the inflation and the exchange rate while the nine other stocks do not show the existence of the expected causality. The results of causality test are then estimated by the VAR models in order to obtain expected returnof macroeconomic factors. The expected return of macroeconomic factors obtained is used in the APT model, then the expected return stock LPKR is calculated. It shows that the expected return of LPKR is 3,340%

  18. Very-short-term wind power probabilistic forecasts by sparse vector autoregression

    DEFF Research Database (Denmark)

    Dowell, Jethro; Pinson, Pierre

    2016-01-01

    A spatio-temporal method for producing very-shortterm parametric probabilistic wind power forecasts at a large number of locations is presented. Smart grids containing tens, or hundreds, of wind generators require skilled very-short-term forecasts to operate effectively, and spatial information...... is highly desirable. In addition, probabilistic forecasts are widely regarded as necessary for optimal power system management as they quantify the uncertainty associated with point forecasts. Here we work within a parametric framework based on the logit-normal distribution and forecast its parameters....... The location parameter for multiple wind farms is modelled as a vector-valued spatiotemporal process, and the scale parameter is tracked by modified exponential smoothing. A state-of-the-art technique for fitting sparse vector autoregressive models is employed to model the location parameter and demonstrates...

  19. Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

    Science.gov (United States)

    Price, Larry R.

    2012-01-01

    The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

  20. Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models

    DEFF Research Database (Denmark)

    Cavaliere, G.; Rahbek, Anders; Taylor, A.M.R.

    2014-01-01

    In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying vector autoregressive (VAR) model which obtain under the reduced rank null hypothesis. They propose methods based on an independent and individual distributed (i.i.d.) bootstrap resampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co......-integrated VAR model with i.i.d. innovations. In this paper we investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap resampling scheme, when time-varying behavior is present in either the conditional or unconditional variance of the innovations. We...

  1. Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Callot, Laurent

    We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated consistently...

  2. Business cycles and fertility dynamics in the United States: a vector autoregressive model.

    Science.gov (United States)

    Mocan, N H

    1990-01-01

    "Using vector-autoregressions...this paper shows that fertility moves countercyclically over the business cycle....[It] shows that the United States fertility is not governed by a deterministic trend as was assumed by previous studies. Rather, fertility evolves around a stochastic trend. It is shown that a bivariate analysis between fertility and unemployment yields a procyclical picture of fertility. However, when one considers the effects on fertility of early marriages and the divorce behavior as well as economic activity, fertility moves countercyclically." excerpt

  3. The cointegrated vector autoregressive model with general deterministic terms

    DEFF Research Database (Denmark)

    Johansen, Søren; Nielsen, Morten Ørregaard

    2017-01-01

    In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)=Z(t) Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are X 2 -distributed....

  4. The cointegrated vector autoregressive model with general deterministic terms

    DEFF Research Database (Denmark)

    Johansen, Søren; Nielsen, Morten Ørregaard

    In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)= Z(t) + Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are khi squared distributed....

  5. Bias-Correction in Vector Autoregressive Models: A Simulation Study

    Directory of Open Access Journals (Sweden)

    Tom Engsted

    2014-03-01

    Full Text Available We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find that it compares very favorably in non-stationary models.

  6. Inflation adjustment in the open economy

    DEFF Research Database (Denmark)

    Nielsen, Heino Bohn; Bowdler, Christopher

    2006-01-01

    This paper estimates a cointegrated vector autoregressive (VAR) model for UK data on consumer prices, unit labour costs, import prices and real consumption growth. The estimated VAR indicates that the nominal variables are characterised by I(2) trends, and that a linear combination of these proce......This paper estimates a cointegrated vector autoregressive (VAR) model for UK data on consumer prices, unit labour costs, import prices and real consumption growth. The estimated VAR indicates that the nominal variables are characterised by I(2) trends, and that a linear combination...

  7. Inflows and their Macroeconomic Impact in India a VAR Analysis

    Directory of Open Access Journals (Sweden)

    Narayan Sethi

    2012-12-01

    Full Text Available The present study attempts to examine the effects of private foreign capital inflows (FINV on macroeconomic variables in India. The study also examines the trends and composition of capital inflows into India. Using the Vector Autoregression (VAR method, this paper specifically examines effects of private foreign capital inflows (FINV on macroeconomic variables in India. This study is based on the monthly data from 1995:04 to 2011:07 and incorporating the macroeconomic variables such as exchange rate (EXR, inflation, money supply (M3, export (EXPO, import (IMP, foreign exchange reserve (FOREX and economic growth (IIP as proxy of GDP. The important observations emerge from the VAR analysis which shows there is dynamic short and long equilibrium relationship between few macroeconomic variables like exchange rate (EXR, foreign exchange reserve (FOREX, index of industrial production (IIP and money supply (M3 with private foreign capital inflows (FINV during the study period from 1995:04 to 2011:07

  8. Vector Autoregressive Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example.

    Science.gov (United States)

    Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M

    Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display interrelated vital sign changes during situations of physiological stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. The purpose of this article is to illustrate the development of patient-specific VAR models using vital sign time series data in a sample of acutely ill, monitored, step-down unit patients and determine their Granger causal dynamics prior to onset of an incident CRI. CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40-140/minute, RR = 8-36/minute, SpO2 time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity, (b) appropriate lag was determined using a lag-length selection criteria, (c) the VAR model was constructed, (d) residual autocorrelation was assessed with the Lagrange Multiplier test, (e) stability of the VAR system was checked, and (f) Granger causality was evaluated in the final stable model. The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%; i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18%). Within this sample of acutely ill patients who experienced a CRI event, VAR modeling indicated that RR changes

  9. Integration of Financial Markets in Post Global Financial Crises and Implications for British Financial Sector: Analysis Based on A Panel VAR Model

    OpenAIRE

    Nasir, M; Du, M

    2017-01-01

    This study analyses the dynamics of integration among global financial markets in the context of Global Financial Crisis (2008) by employing a Panel Vector Autoregressive (VAR) model on the monthly data of nine countries and three markets from Jan 2003 to Oct 2015. It was found that there has been a shift in the association among the global financial markets since Global Financial Crisis (GFC).Moreover, the British financial sectors in Post-GFC world clearly showed a change in the association...

  10. Analysis of Budget Deficits and Macroeconomic Fundamentals: A VAR-VECM Approach

    Directory of Open Access Journals (Sweden)

    Manamba Epaphra

    2017-10-01

    Full Text Available Aim/purpose - This paper examines the relationship between budget deficits and selected macroeconomic variables in Tanzania for the period spanning from 1966 to 2015. Design/methodology/approach - The paper uses Vector autoregression (VAR - Vector Error Correction Model (VECM and variance decomposition techniques. The Johansen's test is applied to examine the long run relationship among the variables under study. Findings - The Johansen's test of cointegration indicates that the variables are cointegrated and thus have a long run relationship. The results based on the VAR-VECM estimation show that real GDP and exchange rate have a negative and significant relationship with budget deficit whereas inflation, money supply and lending interest rate have a positive one. Variance decomposition results show that variances in the budget deficits are mostly explained by the real GDP, followed by inflation and real exchange rate. Research implications/limitations - Results are very indicative, but highlight the importance of containing inflation and money supply to check their effects on budget deficits over the short run and long-run periods. Also, policy recommendation calls for fiscal authorities in Tanzania to adopt efficient and effective methods of tax collection and public sector spending. Originality/value/contribution - Tanzania has been experiencing budget deficit since the 1970s and that this budget deficit has been blamed for high indebtedness, inflation and poor investment and growth. The paper contributes to the empirical debate on the causal relationship between budget deficits and macroeconomic variables by employing VAR-VECM and variance decomposition approaches.

  11. On The Value at Risk Using Bayesian Mixture Laplace Autoregressive Approach for Modelling the Islamic Stock Risk Investment

    Science.gov (United States)

    Miftahurrohmah, Brina; Iriawan, Nur; Fithriasari, Kartika

    2017-06-01

    Stocks are known as the financial instruments traded in the capital market which have a high level of risk. Their risks are indicated by their uncertainty of their return which have to be accepted by investors in the future. The higher the risk to be faced, the higher the return would be gained. Therefore, the measurements need to be made against the risk. Value at Risk (VaR) as the most popular risk measurement method, is frequently ignore when the pattern of return is not uni-modal Normal. The calculation of the risks using VaR method with the Normal Mixture Autoregressive (MNAR) approach has been considered. This paper proposes VaR method couple with the Mixture Laplace Autoregressive (MLAR) that would be implemented for analysing the first three biggest capitalization Islamic stock return in JII, namely PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK), and PT. Unilever Indonesia Tbk (UNVR). Parameter estimation is performed by employing Bayesian Markov Chain Monte Carlo (MCMC) approaches.

  12. IDENTIFYING BANK LENDING CHANNEL IN INDONESIA: A VECTOR ERROR CORRECTION APPROACH WITH STRUCTURAL BREAK

    Directory of Open Access Journals (Sweden)

    Akhsyim Afandi

    2017-03-01

    Full Text Available There was a question whether monetary policy works through bank lending channelrequired a monetary-induced change in bank loans originates from the supply side. Mostempirical studies that employed vector autoregressive (VAR models failed to fulfill thisrequirement. Aiming to offer a solution to this identification problem, this paper developed afive-variable vector error correction (VEC model of two separate bank credit markets inIndonesia. Departing from previous studies, the model of each market took account of onestructural break endogenously determined by implementing a unit root test. A cointegrationtest that took account of one structural break suggested two cointegrating vectors identifiedas bank lending supply and demand relations. The estimated VEC system for both marketssuggested that bank loans adjusted more strongly in the direction of the supply equation.

  13. Exploiting the cointegration properties of U.S. pork - related markets

    DEFF Research Database (Denmark)

    Babula, Ronald; Lund, Mogens

    We apply methods of the cointegrated vector autoregression or VAR model to quar-terly U.S. pork-related markets, from the farm gate upstream, to the downstream markets for processed pork and sausage. This study extends prior VAR econometric work by concentrating on the upstream/downstream relatio......We apply methods of the cointegrated vector autoregression or VAR model to quar-terly U.S. pork-related markets, from the farm gate upstream, to the downstream markets for processed pork and sausage. This study extends prior VAR econometric work by concentrating on the upstream....../downstream relationships between the U.S. farm market for pork and markets for processed pork and sausage. Results include a U.S. long run demand for pork, as well as empirical estimates of specific market events on these three pork-related markets....

  14. Oil Price Volatility and Economic Growth in Nigeria: a Vector Auto-Regression (VAR Approach

    Directory of Open Access Journals (Sweden)

    Edesiri Godsday Okoro

    2014-02-01

    Full Text Available The study examined oil price volatility and economic growth in Nigeria linking oil price volatility, crude oil prices, oil revenue and Gross Domestic Product. Using quarterly data sourced from the Central Bank of Nigeria (CBN Statistical Bulletin and World Bank Indicators (various issues spanning 1980-2010, a non‐linear model of oil price volatility and economic growth was estimated using the VAR technique. The study revealed that oil price volatility has significantly influenced the level of economic growth in Nigeria although; the result additionally indicated a negative relationship between the oil price volatility and the level of economic growth. Furthermore, the result also showed that the Nigerian economy survived on crude oil, to such extent that the country‘s budget is tied to particular price of crude oil. This is not a good sign for a developing economy, more so that the country relies almost entirely on revenue of the oil sector as a source of foreign exchange earnings. This therefore portends some dangers for the economic survival of Nigeria. It was recommended amongst others that there should be a strong need for policy makers to focus on policy that will strengthen/stabilize the economy with specific focus on alternative sources of government revenue. Finally, there should be reduction in monetization of crude oil receipts (fiscal discipline, aggressive saving of proceeds from oil booms in future in order to withstand vicissitudes of oil price volatility in future.

  15. Modelling cointegration in the vector autoregressive model

    DEFF Research Database (Denmark)

    Johansen, Søren

    2000-01-01

    A survey is given of some results obtained for the cointegrated VAR. The Granger representation theorem is discussed and the notions of cointegration and common trends are defined. The statistical model for cointegrated I(1) variables is defined, and it is shown how hypotheses on the cointegratin...

  16. THE DETERMINANTS OF STOCK MARKET INDEX: VAR APPROACH TO TURKISH STOCK MARKET

    Directory of Open Access Journals (Sweden)

    Eşref Savaş Başçı

    2013-01-01

    Full Text Available In this paper, we examined the relationship between ISE 100 Index and a set of four macroeconomic variables using Vector Autoregressive (VAR model. Variables we used in our model are Exchange, Gold, Import, Export and ISE 100 Index. ISE 100 Index is a dependent variable and the others are independent variables. In this study we used 190 observations for the sample period from January, 1996 to October, 2011. All variables have seasonal movements. After seasonal adjustments, all series have had stationary in their first difference. After determining optimal lag order, it was given one standard deviation shock for each series and their response. And in variance decomposition carried out subsequently, it has been determined that especially as of the second default of exchange, it was explained 31% by share indices.

  17. Forecasting daily political opinion polls using the fractionally cointegrated VAR model

    DEFF Research Database (Denmark)

    Nielsen, Morten Ørregaard; Shibaev, Sergei S.

    We examine forecasting performance of the recent fractionally cointegrated vector autoregressive (FCVAR) model. We use daily polling data of political support in the United Kingdom for 2010-2015 and compare with popular competing models at several forecast horizons. Our findings show that the four...... trend from the model follows the vote share of the UKIP very closely, and we thus interpret it as a measure of Euro-skepticism in public opinion rather than an indicator of the more traditional left-right political spectrum. In terms of prediction of vote shares in the election, forecasts generated...... variants of the FCVAR model considered are generally ranked as the top four models in terms of forecast accuracy, and the FCVAR model significantly outperforms both univariate fractional models and the standard cointegrated VAR (CVAR) model at all forecast horizons. The relative forecast improvement...

  18. Presencia en Isla Fuerte, Bolívar de Lutzomyia evansi vector de leishmaniosis visceral Presense of lutzomyia evansi vector of visceral leishmaniosis in Isla Fuerte, Colombia

    Directory of Open Access Journals (Sweden)

    Ivan Darío Vélez

    1994-01-01

    Full Text Available Se hizo un Inventario de fauna flebotomínea en Isla Fuerte, Bolívar, costa caribe colombiana. Se demostró por primera vez en dicha Isla la presencia de Lu. evansi, Lu. gomezi y Lu. trinidadensis. La presencia de Lu. Evansi (91.7% de las 73 capturas, vector principal de la leishmaniosis visceral en la costa caribe colombiana, convierte a Isla Fuerte en una zona de riesgo potencial de transmisión de leishmaniosis visceral.

    An inventory was made of phiebotomidae fauna in Isla Fuerte, Bolívar, on the caribbean colombian coast. The presence of Lu. evansi was demonstrated for the first time in that island and this species constituted 91.7% of 73 captures. Therefore the island becomes a potential risk for transmission of visceralleish. maniosis since Lu. evansi its main vector.

  19. Sensor network based solar forecasting using a local vector autoregressive ridge framework

    Energy Technology Data Exchange (ETDEWEB)

    Xu, J. [Stony Brook Univ., NY (United States); Yoo, S. [Brookhaven National Lab. (BNL), Upton, NY (United States); Heiser, J. [Brookhaven National Lab. (BNL), Upton, NY (United States); Kalb, P. [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-04-04

    The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

  20. An extension of cointegration to fractional autoregressive processes

    DEFF Research Database (Denmark)

    Johansen, Søren

    This paper contains an overview of some recent results on the statistical analysis of cofractional processes, see Johansen and Nielsen (2010). We first give an brief summary of the analysis of cointegration in the vector autoregressive model and then show how this can be extended to fractional pr...

  1. Evidence on a Real Business Cycle Model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging

    NARCIS (Netherlands)

    R.W. Strachan (Rodney); H.K. van Dijk (Herman)

    2010-01-01

    textabstractThe empirical support for a real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure. This procedure makes use of a finite mixture of many models within the class of vector autoregressive (VAR) processes. The linear VAR model is

  2. Estimation bias and bias correction in reduced rank autoregressions

    DEFF Research Database (Denmark)

    Nielsen, Heino Bohn

    2017-01-01

    This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

  3. Identification of Civil Engineering Structures using Vector ARMA Models

    DEFF Research Database (Denmark)

    Andersen, P.

    The dissertation treats the matter of systems identification and modelling of load-bearing constructions using Auto-Regressive Moving Average Vector (ARMAV) models.......The dissertation treats the matter of systems identification and modelling of load-bearing constructions using Auto-Regressive Moving Average Vector (ARMAV) models....

  4. A comparison of the VAR model and the PC factor model in forecasting inflation in Montenegro

    Directory of Open Access Journals (Sweden)

    Lipovina-Božović Milena

    2013-01-01

    Full Text Available Montenegro started using the euro in 2002 and regained independence in 2006. Its main economic partners are European countries, yet inflation movements in Montenegro do not coincide with consumer price fluctuations in the eurozone. Trying to develop a useful forecasting model for Montenegrin inflation, we compare the results of a three-variable vector autoregression (VAR model, and a principle component (PC factor model starting with twelve variables. The estimation period is January 2001 to December 2012, and the control months are the first six months of 2013. The results show that in forecasting inflation, despite a high level of Montenegrin economic dependence on international developments, more reliable forecasts are achieved with the use of additional information on a larger number of factors, which includes domestic economic activity.

  5. International Trade, Pollution Accumulation and Sustainable Growth: A VAR Estimation from the Pearl River Delta Region

    Science.gov (United States)

    Zuo, Hui; Tian, Lu

    2018-03-01

    In order to investigate international trade influence in the regional environment. This paper constructs a vector auto-regression (VAR) model and estimates the equations with the environment and trade data of the Pearl River Delta Region. The major mechanisms to the lag are discussed and the fit simulation of the environmental change by the international impulse is given. The result shows that impulse of pollution-intensive export deteriorates the environment continuously and impulse of such import improves it. These effects on the environment are insignificantly correlated with contemporary regional income but significantly correlative to early-stage trade feature. To a typical trade-dependent economy, both export and import have hysteresis influence in the regional environment. The lagged impulse will change environmental development in the turning point, maximal pollution level and convergence.

  6. An Examination of the Relationship between Financial Development ...

    African Journals Online (AJOL)

    Nneka Umera-Okeke

    common stochastic trend driving their relationship. ... growth models have explained that the interaction between financial development and ..... This study adopted a dynamic vector autoregressive regression (VAR) which explores ... adjustment parameters in the vector error correction model and each column of is a.

  7. Public Capital and Regional Economic Growth: a SVAR Approach for the Spanish Regions

    Directory of Open Access Journals (Sweden)

    Geoffrey J. D. Hewings

    2011-01-01

    Full Text Available Recently, a significant share of the empirical analysis on the impact of public capital on regional growth has used multivariate time-series frameworks based on vector autoregressive (VAR models. Nevertheless, not as much attention has been dedicated to the analysis of the long-run determinants of regional growth processes using multi-region panel data and applying panel integration and co-integration techniques. This paper estimates the dynamic domestic effects of public infrastructure using a structural vector autoregressive (S-VAR methodology for the Spanish regions. From a methodological point of view, the paper contains several features that can be viewed as a contribution to the existing empirical literature. First, the important issues of the stationarity of the data and the existence and estimation of cointegrating relationships in the long-run are addressed in the context of the analysis of panel data. Secondly, the long-run cointegrating production function is embedded within structural vector error correction (S-VEC shortrun models to produce consistent estimates of impulse responses, contrary to many researchers who have estimated unrestricted VAR models in levels or VAR models in first differences. The estimates reveal new results with respect to the previous empirical evidence.

  8. Kronecker-ARX models in identifying (2D) spatial-temporal systems

    NARCIS (Netherlands)

    Sinquin, B.; Verhaegen, M.H.G.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    In this paper we address the identification of (2D) spatial-temporal dynamical systems governed by the Vector Auto-Regressive (VAR) form. The coefficient-matrices of the VAR model are parametrized as sums of Kronecker products. When the number of terms in the sum is small compared to the size of

  9. Afrika Statistika ISSN 2316-090X Multivariate Analysis of Rwanda ...

    African Journals Online (AJOL)

    Consumer Price Index (CPI), Exchange Rate and Nominal Growth. Domestic ... Economic Indicators using Vector Autoregressive (VAR) Model. 1540 ... useful for describing the dynamic behavior of economic and financial time series and for.

  10. Exploring the transformation and upgrading of China's economy using electricity consumption data: A VAR-VEC based model

    Science.gov (United States)

    Zhang, Chi; Zhou, Kaile; Yang, Shanlin; Shao, Zhen

    2017-05-01

    Since the reforming and opening up in 1978, China has experienced a miraculous development. To investigate the transformation and upgrading of China's economy, this study focuses on the relationship between economic growth and electricity consumption of the secondary and tertiary industry in China. This paper captures the dynamic interdependencies among the related variables using a theoretical framework based on a Vector Autoregressive (VAR)-Vector Error Correction (VEC) model. Using the macroeconomic and electricity consumption data, the results show that, for secondary industry, there is only a unidirectional Granger causality from electricity consumption to Gross Domestic Product (GDP) from 1980 to 2000. However, for the tertiary industry, it only occurs that GDP Granger causes electricity consumption from 2001 to 2014. All these conclusions are verified by the impulse response function and variance decomposition. This study has a great significance to reveal the relationship between industrial electricity consumption and the pattern of economic development. Meanwhile, it further suggests that, since China joined the World Trade Organization (WTO) in 2001, the trend of the economic transformation and upgrading has gradually appeared.

  11. Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

    Science.gov (United States)

    Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

    2016-11-01

    Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

  12. Thresholds and Smooth Transitions in Vector Autoregressive Models

    DEFF Research Database (Denmark)

    Hubrich, Kirstin; Teräsvirta, Timo

    This survey focuses on two families of nonlinear vector time series models, the family of Vector Threshold Regression models and that of Vector Smooth Transition Regression models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the...

  13. Nonlinear dynamic interrelationships between real activity and stock returns

    DEFF Research Database (Denmark)

    Lanne, Markku; Nyberg, Henri

    We explore the differences between the causal and noncausal vector autoregressive (VAR) models in capturing the real activity-stock return-relationship. Unlike the conventional linear VAR model, the noncausal VAR model is capable of accommodating various nonlinear characteristics of the data....... In quarterly U.S. data, we find strong evidence in favor of noncausality, and the best causal and noncausal VAR models imply quite different dynamics. In particular, the linear VAR model appears to underestimate the importance of the stock return shock for the real activity, and the real activity shock...

  14. Modeling vector nonlinear time series using POLYMARS

    NARCIS (Netherlands)

    de Gooijer, J.G.; Ray, B.K.

    2003-01-01

    A modified multivariate adaptive regression splines method for modeling vector nonlinear time series is investigated. The method results in models that can capture certain types of vector self-exciting threshold autoregressive behavior, as well as provide good predictions for more general vector

  15. Media-politics interaction in times of economic crisis: a comparative study of Spain and the Netherlands

    NARCIS (Netherlands)

    Vliegenthart, R.; Mena, N.

    2013-01-01

    This paper investigates the multi-directional causal relationships between stock market ratings, negative economic coverage in two national newspapers and parliamentary questions addressing negative aspects of the economy in Spain and the Netherlands. Weekly-level Vector Autoregression (VAR)

  16. Poisson Autoregression

    DEFF Research Database (Denmark)

    Fokianos, Konstantinos; Rahbek, Anders Christian; Tjøstheim, Dag

    2009-01-01

    In this article we consider geometric ergodicity and likelihood-based inference for linear and nonlinear Poisson autoregression. In the linear case, the conditional mean is linked linearly to its past values, as well as to the observed values of the Poisson process. This also applies...... to the conditional variance, making possible interpretation as an integer-valued generalized autoregressive conditional heteroscedasticity process. In a nonlinear conditional Poisson model, the conditional mean is a nonlinear function of its past values and past observations. As a particular example, we consider...... an exponential autoregressive Poisson model for time series. Under geometric ergodicity, the maximum likelihood estimators are shown to be asymptotically Gaussian in the linear model. In addition, we provide a consistent estimator of their asymptotic covariance matrix. Our approach to verifying geometric...

  17. Oil price fluctuations and their impact on the macroeconomic variables of Kuwait: a case study using a VAR model

    International Nuclear Information System (INIS)

    Eltony, M. Nagy; Al-Awadi, Mohammad

    2001-01-01

    In this study, a vector autoregression model (VAR) and a vector error correction model (VECM) were estimated to examine the impact of oil price fluctuations on seven key macroeconomic variables for the Kuwaiti economy. Quarterly data for the period 1984-1998 were utilised. Theoretically and empirically speaking, VECM is superior to the VAR approach. Also, the results corresponding to the VECM model are closer to common sense. However, the estimated models indicate a high degree of interrelation between major macroeconomic variables. The empirical results highlight the causality running from the oil prices and oil revenues, to government development and current expenditure and then towards other variables. For the most part, the empirical evidence indicates that oil price shocks and hence oil revenues have a notable impact on government expenditure, both development and current. However, government development expenditure has been influenced relatively more. The results also point out the significant of the CPI in explaining a notable part of the variations of both types of government expenditure. On the other hand, the variations in value of imports are mostly accounted for by oil revenue fluctuations. On the other hand, the variations in value of imports are mostly accounted for by oil revenue fluctuations and then by the fluctuation in government development expenditures. Also, the results from the VECM approach indicate that a significant part of LM2 variance is explained by the variance in oil revenue. It reaches about 46 per cent in the 10th quarter, even more than its own variations. (Author)

  18. Pooling data for the analysis of dynamic marketing systems

    NARCIS (Netherlands)

    Horvath, C.; Wieringa, J.E.

    Vector autoregressive (VAR) models have become popular in marketing literature for analyzing the behavior of competitive marketing systems. One drawback of these models is that the number of parameters can become very large, potentially leading to estimation problems. Pooling data for multiple

  19. Short-term electricity prices forecasting based on support vector regression and Auto-regressive integrated moving average modeling

    International Nuclear Information System (INIS)

    Che Jinxing; Wang Jianzhou

    2010-01-01

    In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the ε-insensitive loss function, admits of the residual within the boundary values of ε-tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.

  20. Kumaraswamy autoregressive moving average models for double bounded environmental data

    Science.gov (United States)

    Bayer, Fábio Mariano; Bayer, Débora Missio; Pumi, Guilherme

    2017-12-01

    In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.

  1. The asymmetric effects of oil price and monetary policy shocks. A nonlinear VAR approach

    International Nuclear Information System (INIS)

    Rahman, Sajjadur; Serletis, Apostolos

    2010-01-01

    In this paper we investigate the asymmetric effects of oil price shocks and monetary policy on macroeconomic activity, using monthly data for the United States, over the period from 1983:1 to 2008:12. In doing so, we use a logistic smooth transition vector autoregression (VAR), as detailed in Terasvirta and Anderson (1992) and Weise (1999), and make a distinction between two oil price volatility regimes (high and low), using the realized oil price volatility as a switching variable. We isolate the effects of oil price and monetary policy shocks and their asymmetry on output growth and, following Koop et al. (1996) and Weise (1999), we employ simulation methods to calculate Generalized Impulse Response Functions (GIRFs) to trace the effects of independent shocks on the conditional means of the variables. Our results suggest that in addition to the price of oil, oil price volatility has an impact on macroeconomic activity and that monetary policy is not only reinforcing the effects of oil price shocks on output, it is also contributing to the asymmetric response of output to oil price shocks. (author)

  2. The asymmetric effects of oil price and monetary policy shocks. A nonlinear VAR approach

    Energy Technology Data Exchange (ETDEWEB)

    Rahman, Sajjadur [Department of Economics, University of Saskatchewan, Saskatoon (Canada); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary (Canada)

    2010-11-15

    In this paper we investigate the asymmetric effects of oil price shocks and monetary policy on macroeconomic activity, using monthly data for the United States, over the period from 1983:1 to 2008:12. In doing so, we use a logistic smooth transition vector autoregression (VAR), as detailed in Terasvirta and Anderson (1992) and Weise (1999), and make a distinction between two oil price volatility regimes (high and low), using the realized oil price volatility as a switching variable. We isolate the effects of oil price and monetary policy shocks and their asymmetry on output growth and, following Koop et al. (1996) and Weise (1999), we employ simulation methods to calculate Generalized Impulse Response Functions (GIRFs) to trace the effects of independent shocks on the conditional means of the variables. Our results suggest that in addition to the price of oil, oil price volatility has an impact on macroeconomic activity and that monetary policy is not only reinforcing the effects of oil price shocks on output, it is also contributing to the asymmetric response of output to oil price shocks. (author)

  3. The Regional Impact of Monetary Policy in Indonesia

    NARCIS (Netherlands)

    Ridhwan, M.M.; de Groot, H.L.F.; Rietveld, P.; Nijkamp, P.

    2014-01-01

    This paper employs vector autoregressive (VAR) models to measure the impact of monetary policy shocks on regional output in Indonesia. We find substantial cross-regional variation in policy responses in terms of both magnitude as well as timing. Our work adds to the existing literature by providing

  4. Predicting downturns in the US housing market: a Bayesian approach

    CSIR Research Space (South Africa)

    Gupta, R

    2010-10-01

    Full Text Available one-to-four quarters-ahead real house price growth over the out-of- sample horizon of 1995:Q1–2006:Q4. The forecasts are evaluated by comparing them with those from an unrestricted classical Vector Autoregressive (VAR) model and the corresponding...

  5. Poisson Autoregression

    DEFF Research Database (Denmark)

    Fokianos, Konstantinos; Rahbek, Anders Christian; Tjøstheim, Dag

    This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process. This also applies to the conditional...... variance, implying an interpretation as an integer valued GARCH process. In a nonlinear conditional Poisson model, the conditional mean is a nonlinear function of its past values and a nonlinear function of past observations. As a particular example an exponential autoregressive Poisson model for time...

  6. Poisson Autoregression

    DEFF Research Database (Denmark)

    Fokianos, Konstantinos; Rahbæk, Anders; Tjøstheim, Dag

    This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process. This also applies to the conditional...... variance, making an interpretation as an integer valued GARCH process possible. In a nonlinear conditional Poisson model, the conditional mean is a nonlinear function of its past values and a nonlinear function of past observations. As a particular example an exponential autoregressive Poisson model...

  7. A fractionally cointegrated VAR analysis of economic voting and political support

    DEFF Research Database (Denmark)

    Jones, Maggie E. C.; Ørregård Nielsen, Morten; Popiel, Michael Ksawery

    We use a fractionally cointegrated vector autoregressive model to examine the relationship between Canadian political support and macroeconomic conditions. This model is well suited for the analysis because it allows multiple fractional time series and admits simple asymptotic inference for the m......We use a fractionally cointegrated vector autoregressive model to examine the relationship between Canadian political support and macroeconomic conditions. This model is well suited for the analysis because it allows multiple fractional time series and admits simple asymptotic inference...... for the model parameters and tests of the hypotheses of interest. In the long-run equilibrium, we find that support for the Progressive Conservative Party was higher during periods of high interest rates and low unemployment, while support for the Liberal Party was higher during periods of low interest rates...

  8. Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

    Science.gov (United States)

    Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

    2016-07-01

    Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

  9. IS IT REAL - THE RELATIONSHIP BETWEEN VEAL DEFICITS AND REAL GROWTH - NEW EVIDENCE USING LONG-RUN DATA

    NARCIS (Netherlands)

    DEHAAN, J; STURM, JE

    Long-run data for the USA is used to examine whether the inflation adjustment of the government budget deficit as proposed by Eisner and Pieper makes a difference in assessing the impact of fiscal policy on economic growth. Using Vector Autoregressions (VAR) it is found that both the inflation

  10. Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratios and Liquidity Trap Risk

    NARCIS (Netherlands)

    R.W. Strachan (Rodney); H.K. van Dijk (Herman)

    2008-01-01

    textabstractA Bayesian model averaging procedure is presented that makes use of a finite mixture of many model structures within the class of vector autoregressive (VAR) processes. It is applied to two empirical issues. First, stability of the Great Ratios in U.S. macro-economic time series is

  11. Estimating the equilibrium real exchange rate in Venezuela

    OpenAIRE

    Hilde Bjørnland

    2004-01-01

    To determine whether the real exchange rate is misaligned with respect to its long-run equilibrium is an important issue for policy makers. This paper clarifies and calculates the concept of the equilibrium real exchange rate, using a structural vector autoregression (VAR) model. By imposing long-run restrictions on a VAR model for Venezuela, four structural shocks are identified: Nominal demand, real demand, supply and oil price shocks. The identified shocks and their impulse responses are c...

  12. The impact of media campaigns on smoking cessation activity: a structural vector autoregression analysis.

    Science.gov (United States)

    Langley, Tessa E; McNeill, Ann; Lewis, Sarah; Szatkowski, Lisa; Quinn, Casey

    2012-11-01

    To evaluate the effect of tobacco control media campaigns and pharmaceutical company-funded advertising for nicotine replacement therapy (NRT) on smoking cessation activity. Multiple time series analysis using structural vector autoregression, January 2002-May 2010. England and Wales. Tobacco control campaign data from the Central Office of Information; commercial NRT campaign data; data on calls to the National Health Service (NHS) stop smoking helpline from the Department of Health; point-of-sale data on over-the-counter (OTC) sales of NRT; and prescribing data from The Health Improvement Network (THIN), a database of UK primary care records. Monthly calls to the NHS stop smoking helpline and monthly rates of OTC sales and prescribing of NRT. A 1% increase in tobacco control television ratings (TVRs), a standard measure of advertising exposure, was associated with a statistically significant 0.085% increase in calls in the same month (P = 0.007), and no statistically significant effect in subsequent months. Tobacco control TVRs were not associated with OTC NRT sales or prescribed NRT. NRT advertising TVRs had a significant effect on NRT sales which became non-significant in the seasonally adjusted model, and no significant effect on prescribing or calls. Tobacco control campaigns appear to be more effective at triggering quitting behaviour than pharmaceutical company NRT campaigns. Any effect of such campaigns on quitting behaviour seems to be restricted to the month of the campaign, suggesting that such campaigns need to be sustained over time. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  13. political stability and tax power

    OpenAIRE

    Estrada, Fernando

    2013-01-01

    The present study is, in particular, an attempt to test the relationship between tax level and political stability by using some economic control variables and to see the relationship among government effectiveness, corruption, and GDP. For the purpose, we used the Vector Autoregression (VAR) approach in the panel framework, using a country-level panel data from 59 countries for the period 2002 to 2008. The salient features of this model are: (a) simplicity is based on a limited number of var...

  14. Taxation and political stability

    OpenAIRE

    Estrada, Fernando; Mutascu, Mihai; Tiwari, Aviral

    2011-01-01

    The present study is, in particular, an attempt to test the relationship between tax level and political stability by using some economic control variables and to see the relationship among government effectiveness, corruption, and GDP. For the purpose, we used the Vector Autoregression (VAR) approach in the panel framework, using a country-level panel data from 59 countries for the period 2002 to 2008. The salient features of this model are: (a) simplicity is based on a limited number of var...

  15. Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

    Science.gov (United States)

    Lohani, A. K.; Kumar, Rakesh; Singh, R. D.

    2012-06-01

    SummaryTime series modeling is necessary for the planning and management of reservoirs. More recently, the soft computing techniques have been used in hydrological modeling and forecasting. In this study, the potential of artificial neural networks and neuro-fuzzy system in monthly reservoir inflow forecasting are examined by developing and comparing monthly reservoir inflow prediction models, based on autoregressive (AR), artificial neural networks (ANNs) and adaptive neural-based fuzzy inference system (ANFIS). To take care the effect of monthly periodicity in the flow data, cyclic terms are also included in the ANN and ANFIS models. Working with time series flow data of the Sutlej River at Bhakra Dam, India, several ANN and adaptive neuro-fuzzy models are trained with different input vectors. To evaluate the performance of the selected ANN and adaptive neural fuzzy inference system (ANFIS) models, comparison is made with the autoregressive (AR) models. The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows. In all cases ANFIS gives more accurate forecast than the AR and ANN models. The proposed ANFIS model coupled with the cyclic terms is shown to provide better representation of the monthly inflow forecasting for planning and operation of reservoir.

  16. The impact of remittances outflows on the economy of Poland

    OpenAIRE

    LASTOVETSKA ROKSOLANA ORESTIVNA

    2015-01-01

    The impact of remittances outflows on the economy of Poland is analyzed in the article. Based on historical data the vector autoregression model (VAR) was built to examine the effects of the sharp rise in the volume of remittances outflows. The model results are presented for the next macroeconomic indicators: GDP, inflation, interest rate and exchange rate.

  17. Analysis of Influence Factors of PM2.5 in Chengdu Based on VAR Model

    Science.gov (United States)

    Mingzhi, Luo

    2017-05-01

    Air pollution and smog are the serious harms to public health and has attracted public attention. Based on the vector auto-regressive (VAR) model, we analysed the influence factors of PM2.5 in Chengdu, investigated the effect of other kinds of air pollutants and meteorological factors onthe PM2.5 by using the methods of generalized impulse response function, variance decomposition analysis, Granger causality test and therelated daily data from December 1, 2013 to November 14, 2016 in Chengdu city to the empirical study. The resultsshow that the influence factors of PM2.5 were stable;the increase of nitrogen dioxide, ozone,precipitation and temperature difference led to the increase of PM2.5 concentration while the increase ofthe wind speed, PM10, sulphur dioxide and carbon monoxide resulted in the decrease of PM2.5 concentration.Climate conditions,nitrogen dioxide and ozone are Granger causes for PM2.5.It is suggestedthat the key for the control of PM2.5 must be based on the cause and formation rules of PM2.5.A further study on nitrogen dioxide and ozone may play an important role in finding out the real source and formation reasons of PM2.5.

  18. The relationship between renewable energy assets and crude oil prices : an empirical analysis with emphasis on the effects of the financial crisis

    OpenAIRE

    Grøm, Halvdan Alexander

    2013-01-01

    In this thesis I have analysed the relationship between renewable energy stocks and the price of crude oil. As a part of my analysis I have provided a basic economic overview of the research period and how the value of renewable energy stocks and crude oil is determined. In order to analyse this relationship I have utilized a Vector Autoregressive Model (VAR) in addition to a Vector Error Correction Model (VECM). My findings indicate that the aforementioned assets follow a simi...

  19. Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

    Science.gov (United States)

    Khan, Muhammad Yousaf; Mittnik, Stefan

    2018-01-01

    In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

  20. Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model

    International Nuclear Information System (INIS)

    Xu, Bin; Lin, Boqiang

    2016-01-01

    Highlights: • We explore the driving forces of the iron and steel industry’s CO 2 emissions in China. • Energy efficiency plays a dominant role in reducing carbon dioxide emissions. • Urbanization has significant effect on CO 2 emissions due to mass real estate construction. • The role of economic growth in reducing emissions is more important than industrialization. - Abstract: Energy saving and carbon dioxide emission reduction in China is attracting increasing attention worldwide. At present, China is in the phase of rapid urbanization and industrialization, which is characterized by rapid growth of energy consumption and carbon dioxide (CO 2 ) emissions. China’s steel industry is highly energy-consuming and pollution-intensive. Between 1980 and 2013, the carbon dioxide emissions in China’s steel industry increased approximately 11 times, with an average annual growth rate of 8%. Identifying the drivers of carbon dioxide emissions in the iron and steel industry is vital for developing effective environmental policies. This study uses Vector Autoregressive model to analyze the influencing factors of the changes in carbon dioxide emissions in the industry. The results show that energy efficiency plays a dominant role in reducing carbon dioxide emissions. Urbanization also has significant effect on CO 2 emissions because of mass urban infrastructure and real estate construction. Economic growth has more impact on emission reduction than industrialization due to the massive fixed asset investment and industrial energy optimization. These findings are important for the relevant authorities in China in developing appropriate energy policy and planning for the iron and steel industry.

  1. Causality relation between the producer price index and the consumer price index. Ecuador Case

    Directory of Open Access Journals (Sweden)

    Víctor Quinde Rosales

    2018-01-01

    Full Text Available The present document is an investigation with a type of inductive reasoning. It evaluated the relationship of causality between the producer price index (IPP, and the consumer price index (IPC in a period from January 1998 to December 2016. The unit root test Dickey-Fuller Augmented (DFA was used under an empirical- analytic paradigm, an autoregressive vector-VAR model was generated and the Granger causality test was performed. The results show a positive trend and seasonality in the data of the variables, a VAR model of two variables was obtained with a number of optimal remnants of fourteen VAR2 (14 to which the causality test was performed, demonstrating a bi - directionality of both indices.

  2. Formula I(1 and I(2: Race Tracks for Likelihood Maximization Algorithms of I(1 and I(2 Cointegrated VAR Models

    Directory of Open Access Journals (Sweden)

    Jurgen A. Doornik

    2017-11-01

    Full Text Available This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1 and I(2 models are considered. The performance of algorithms is compared first in terms of effectiveness, defined as the ability to find the overall maximum. The next step is to compare their efficiency and reliability across experiments. The aim of the paper is to commence a collective learning project by the profession on the actual properties of algorithms for cointegrated vector autoregressive model estimation, in order to improve their quality and, as a consequence, also the reliability of empirical research.

  3. THE CORN-EGG PRICE TRANSMISSION MECHANISM

    OpenAIRE

    Babula, Ronald A.; Bessler, David A.

    1990-01-01

    A vector autoregression (VAR) model of corn, farm egg, and retail egg prices is estimated and shocked with a corn price increase. Impulse responses in egg prices, t-statistics for the impulse responses, and decompositions of forecast error variance are presented. Analyses of results provide insights on the corn/egg price transmission mechanism and on how corn price shocks pulsate through the egg-related economy.

  4. Tourism Expenditures and Environment in Thailand

    OpenAIRE

    Malliga Sompholkrang

    2014-01-01

    Tourism activities affect the environment of different destinations, which is influenced by different tourists’ consumption. The objective of this study is to examine the relationship between inbound tourist expenditures and three main environmental dimensions, which are carbon dioxide emission from transport, energy demand, and water usage, in Thailand. This paper employs Vector Autoregressive (VAR) models to determine the relationship of variables. Data from Ministry of Energ...

  5. Oil price shocks, stock market, economic activity and employment in Greece

    International Nuclear Information System (INIS)

    Papapetrou, E.

    2001-01-01

    Using a multivariate vector-autoregression (VAR) approach, this paper attempts to shed light into the dynamic relationship among oil prices, real stock prices, interest rates, real economic activity and employment for Greece. The empirical evidence suggests that oil price changes affect real economic activity and employment. Oil prices are important in explaining stock price movements. Stock returns do not lead to changes in real activity and employment

  6. How Rational Are Inflation Expectations? A Vector Autoregression Decomposition of Inflation Forecasts and Their Errors

    National Research Council Canada - National Science Library

    Ladvogt, Timothy

    2002-01-01

    ... the persistence of forecast errors. A reduced form VAR is used to identify potential inefficiencies and then calculate the impulse response functions and variance decompositions of forecasts errors to analyze how shocks to the other endogenous...

  7. Electric power demand forecasting using interval time series. A comparison between VAR and iMLP

    International Nuclear Information System (INIS)

    Garcia-Ascanio, Carolina; Mate, Carlos

    2010-01-01

    Electric power demand forecasts play an essential role in the electric industry, as they provide the basis for making decisions in power system planning and operation. A great variety of mathematical methods have been used for demand forecasting. The development and improvement of appropriate mathematical tools will lead to more accurate demand forecasting techniques. In order to forecast the monthly electric power demand per hour in Spain for 2 years, this paper presents a comparison between a new forecasting approach considering vector autoregressive (VAR) forecasting models applied to interval time series (ITS) and the iMLP, the multi-layer perceptron model adapted to interval data. In the proposed comparison, for the VAR approach two models are fitted per every hour, one composed of the centre (mid-point) and radius (half-range), and another one of the lower and upper bounds according to the interval representation assumed by the ITS in the learning set. In the case of the iMLP, only the model composed of the centre and radius is fitted. The other interval representation composed of the lower and upper bounds is obtained from the linear combination of the two. This novel approach, obtaining two bivariate models each hour, makes possible to establish, for different periods in the day, which interval representation is more accurate. Furthermore, the comparison between two different techniques adapted to interval time series allows us to determine the efficiency of these models in forecasting electric power demand. It is important to note that the iMLP technique has been selected for the comparison, as it has shown its accuracy in forecasting daily electricity price intervals. This work shows the ITS forecasting methods as a potential tool that will lead to a reduction in risk when making power system planning and operational decisions. (author)

  8. Implementing Modifed Burg Algorithms in Multivariate Subset Autoregressive Modeling

    Directory of Open Access Journals (Sweden)

    A. Alexandre Trindade

    2003-02-01

    Full Text Available The large number of parameters in subset vector autoregressive models often leads one to procure fast, simple, and efficient alternatives or precursors to maximum likelihood estimation. We present the solution of the multivariate subset Yule-Walker equations as one such alternative. In recent work, Brockwell, Dahlhaus, and Trindade (2002, show that the Yule-Walker estimators can actually be obtained as a special case of a general recursive Burg-type algorithm. We illustrate the structure of this Algorithm, and discuss its implementation in a high-level programming language. Applications of the Algorithm in univariate and bivariate modeling are showcased in examples. Univariate and bivariate versions of the Algorithm written in Fortran 90 are included in the appendix, and their use illustrated.

  9. Optimal transformations for categorical autoregressive time series

    NARCIS (Netherlands)

    Buuren, S. van

    1996-01-01

    This paper describes a method for finding optimal transformations for analyzing time series by autoregressive models. 'Optimal' implies that the agreement between the autoregressive model and the transformed data is maximal. Such transformations help 1) to increase the model fit, and 2) to analyze

  10. Testing of the Ricardian Equivalence proposition: An Empirical Examination for Malaysia (1962-2006

    Directory of Open Access Journals (Sweden)

    Ismadi Ismail

    2008-06-01

    Full Text Available This paper investigates the effects of debts and budgetary deficit on real variables using structural Vector Error Correction Model (VECM method with long-run restrictions. We compare our estimates of the impulse responses with those based on levels Vector Auto-Regressive (VAR with standard recursive order restrictions. The test is conducted on the Malaysian data covering the period of 1962-2006. The empirical results do not support the existence of “Ricardian Equivalence” hypothesis. The effects of budgetary deficit and government spending have a significant influence on private consumption and private investment.

  11. INVESTIGATING FINANCIAL INNOVATION AND EUROPEAN CAPITAL MARKETS. THE CASE OF CATASTROPHE BONDS AND LISTED REINSURANCE COMPANIES

    OpenAIRE

    CONSTANTIN LAURA-GABRIELA; CERNAT-GRUICI BOGDAN; IAMANDI IRINA-EUGENIA

    2014-01-01

    Focusing on the financial innovation – stock market interconnections, the present research studies the association between the insurance-linked market activity of European (re)insurance companies and their evolution on the capital markets. With the aim of emphasizing the connections from the perspective of the stock performance and their risk, the empirical analysis is based on vector autoregression (VAR) and Granger causality analyses. The proposed examination is further develope...

  12. RESPONSIVENESS OF SPATIAL PRICE VOLATILITY TO INCREASED GOVERNMENT PARTICIPATION IN MAIZE GRAIN AND MAIZE MEAL MARKETING IN ZAMBIA

    OpenAIRE

    Syampaku, E.M; Mafimisebi, Taiwo Ejiola

    2014-01-01

    The study analyzed the responsiveness of maize grain and maize meal spatial price volatilities to increased government participation in maize grain marketing in Zambia using descriptive statistics and vector auto-regression (VAR). This was achieved by comparing spatial price volatility means and spatial price means for the period under increased government participation with respective means for periods under limited government participation. Also, spatial price volatilities were regressed ag...

  13. The Estimation of the Cointegration Relationship between the Economic Growth, Investments and Exports. The Romanian Case

    Directory of Open Access Journals (Sweden)

    Marius-Corneliu Marinas

    2007-07-01

    Full Text Available This paper attempts to analyze the relationship between exports, investments and economic growth in Romania. For the search of this relationship I use a multivariate autoregressive VAR model. The results of cointegration analysis showed that there is one cointegrated vector among exports, investments and economic growth. Granger causality tests based on error correction models (ECM have indicated that investment and export influences the steady-state level of GDP.

  14. The Effect of Hot Money Flow on Pre-Crisis Indicators of Current Accounts and Real Sectors in Turkish Economy

    OpenAIRE

    Ömer Uğur Bulut; Sadık Rıdvan Karluk

    2016-01-01

    We investigate the impact of the hot money movements on current account and real sector leading crisis indicators under VAR (Vector Autoregressive) framework using quarterly data for a long period of 1991-2014. Our findings show that hot money movements have negative impact on current account deficit and foreign trade deficit pre-crisis indicators. We further show that they lead to instability in growth and inflation pre-crisis indicators.

  15. On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility

    International Nuclear Information System (INIS)

    Jebabli, Ikram; Arouri, Mohamed; Teulon, Frédéric

    2014-01-01

    Transmission of price shocks from one market to another one has long been investigated in the economic literature. However, studies have namely dealt with the relationship between financial and energy markets. With the recent changes in market conditions, investors, policy-makers and interest groups are giving special attention to food market. This paper aims at analyzing shock transmission between international food, energy and financial markets and to provide some insights into the volatility behavior during the past years and discuss its implications for portfolio management. To do this, we present a new time varying parameter VAR (TVP-VAR) model with stochastic volatility approach which provides extreme flexibility with a parsimonious specification. We resort also to a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to the variable ordering for the assessment of total and directional volatility spillovers. Our main findings suggest that volatility spillovers increase considerably during crisis and, namely after mid-2008, when stock markets become net transmitter of volatility shocks while crude oil becomes a net receiver. Shocks to crude oil or MSCI markets have immediate and short-term impacts on food markets which are emphasized during the financial crisis period. Moreover, we show that augmenting a diversified portfolio of food commodities with crude oil or stocks significantly increases its risk-adjusted performance. - Highlights: • We study shock transmission between food, energy and financial markets. • We use a new time-varying parameter VAR model with stochastic volatility. • There is volatility spillover from oil and stock markets to food. • Volatility spillovers increase considerably during crisis, namely after mid-2008. • Augmenting a portfolio of foods with oil or stocks increases its performance

  16. Behavioural Pattern of Causality Parameter of Autoregressive ...

    African Journals Online (AJOL)

    In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...

  17. Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors

    NARCIS (Netherlands)

    Hecq, Alain; Issler, J.V.; Telg, Sean

    2017-01-01

    The mixed autoregressive causal-noncausal model (MAR) has been proposed to estimate economic relationships involving explosive roots in their autoregressive part, as they have stationary forward solutions. In previous work, possible exogenous variables in economic relationships are substituted into

  18. Modelación dinámica de la llegada trimestral de turistas Estadounidenses a México

    Directory of Open Access Journals (Sweden)

    Juan Tello Contreras

    2016-07-01

    Full Text Available The aim of this paper is to identify the economic factors that determine the arrivals of North American tourists to Mexico from a multi-ecuational and dynamic perspective. In particular, long-term relationships and impacts of disposable income, trade value between the two countries and relative prices in the arrival of tourists to Mexico are established. The use of a vector autoregression model (VAR is proposed, the model allows the identification of causal relationships and the forecasting of the quarterly demand of tourists to Mexico for the period 1996-2011. The proposed VAR model accuracy was contrasted against Naïve and SARIMA models.

  19. Study on the Evolution Mechanism and Development Forecasting of China’s Power Supply Structure Clean Development

    Directory of Open Access Journals (Sweden)

    Xiaohua Song

    2017-02-01

    Full Text Available The clean development of China’s power supply structure has become a crucial strategic problem for the low-carbon, green development of Chinese society. Considering the subsistent developments of optimized allocation of energy resources and efficient utilization, the urgent need to solve environmental pollution, and the continuously promoted power market-oriented reform, further study of China’s power structure clean development has certain theoretical value. Based on the data analysis, this paper analyzes the key factors that influence the evolution process of the structure with the help of system dynamics theory and carries out comprehensive assessments after the construction of the structure evaluation system. Additionally, a forecasting model of the power supply structure development based on the Vector Autoregressive Model (VAR has been put forward to forecast the future structure. Through the research of policy review and scenario analysis, the paths and directions of structure optimization are proposed. In this paper, the system dynamics, vector autoregressive model (VAR, policy mining, and scenario analysis methods are combined to systematically demonstrate the evolution of China’s power structure, and predict the future direction of development. This research may provide a methodological and practical reference for the analysis of China’s power supply structure optimization development and for theoretical studies.

  20. Generalizing smooth transition autoregressions

    DEFF Research Database (Denmark)

    Chini, Emilio Zanetti

    We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with part......We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail......, with particular emphasis on two different LM-type tests for the null of symmetric adjustment towards a new regime and three diagnostic tests, whose power properties are explored via Monte Carlo experiments. Four classical real datasets illustrate the empirical properties of the GSTAR, jointly to a rolling...

  1. Tourism Development Policy, Strategic Alliances and Impact of Consumer Price Index on Tourist Arrivals: The Case of Malaysia

    OpenAIRE

    Nanthakumar, Loganathan; Ibrahim, Yahaya; Harun, Madzli

    2007-01-01

    Many studies have shown the importance of tourism industry in enhancing trade performance and economic development. This study examines the hypothesis of ‘economic-driven’ tourism growth in Malaysia by using econometric modelling. To generate the empirical analysis, this study used data from 1980-2007 to analyze the economic-driven tourism growth by using vector autoregressive (VAR) estimation. The long-run relationship between specific variables is considered using the Johansen and Juselius ...

  2. The Empirical Relationship between Mining Industry Development and Environmental Pollution in China

    OpenAIRE

    Li, Gerui; Lei, Yalin; Ge, Jianping; Wu, Sanmang

    2017-01-01

    This study uses a vector autoregression (VAR) model to analyze changes in pollutants among different mining industries and related policy in China from 2001 to 2014. The results show that: (1) because the pertinence of standards for mining waste water and waste gas emissions are not strong and because the maximum permissible discharge pollutant concentrations in these standards are too high, ammonia nitrogen and industrial sulfur dioxide discharges increased in most mining industries; (2) che...

  3. The Effect of Hot Money Flow on Pre-Crisis Indicators of Current Accounts and Real Sectors in Turkish Economy

    Directory of Open Access Journals (Sweden)

    Ömer Uğur Bulut

    2016-12-01

    Full Text Available We investigate the impact of the hot money movements on current account and real sector leading crisis indicators under VAR (Vector Autoregressive framework using quarterly data for a long period of 1991-2014. Our findings show that hot money movements have negative impact on current account deficit and foreign trade deficit pre-crisis indicators. We further show that they lead to instability in growth and inflation pre-crisis indicators.

  4. Granger Causality Testing with Intensive Longitudinal Data.

    Science.gov (United States)

    Molenaar, Peter C M

    2018-06-01

    The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

  5. Efficient transformation and expression of gfp gene in Valsa mali var. mali.

    Science.gov (United States)

    Chen, Liang; Sun, Gengwu; Wu, Shujing; Liu, Huixiang; Wang, Hongkai

    2015-01-01

    Valsa mali var. mali, the causal agent of valsa canker of apple, causes great loss of apple production in apple producing regions. The pathogenic mechanism of the pathogen has not been studied extensively, thus a suitable gene marker for pathogenic invasion analysis and a random insertion of T-DNA for mutants are desirable. In this paper, we reported the construction of a binary vector pKO1-HPH containing a positive selective gene hygromycin phosphotransferase (hph), a reporter gene gfp conferring green fluorescent protein, and an efficient protocol for V. mali var. mali transformation mediated by Agrobacterium tumefaciens. A transformation efficiency up to about 75 transformants per 10(5) conidia was achieved when co-cultivation of V. mali var. mali and A. tumefaciens for 48 h in A. tumefaciens inductive medium agar plates. The insertions of hph gene and gfp gene into V. mali var. mali genome verified by polymerase chain reaction and southern blot analysis showed that 10 randomly-selected transformants exhibited a single, unique hybridization pattern. This is the first report of A. tumefaciens-mediated transformation of V. mali var mali carrying a 'reporter' gfp gene that stably and efficiently expressed in the transformed V. mali var. mali species.

  6. [Susceptibility of Aedes aegypti (L.) strains from Havana to a Bacillus thuringiensis var. israelensis].

    Science.gov (United States)

    Menéndez Díaz, Zulema; Rodríguez Rodríguez, Jinnay; Gato Armas, René; Companioni Ibañez, Ariamys; Díaz Pérez, Manuel; Bruzón Aguila, Rosa Yirian

    2012-01-01

    the integration of chemical and biological methods is one of the strategies for the vector control, due to the existing environmental problems and the concerns of the community as a result of the synthetic organic insecticide actions. The bacterium called Bacillus thuringiensis var. israelensis in liquid formulation has been widely used in the vector control programs in several countries and has shown high efficacy at lab in Cuba. to determine the susceptibility of Aedes aegypti collected in the municipalities of La Habana province to Bacillus thuringiensis var. israelensis. fifteen Aedes aegypti strains, one from each municipality, were used including larvae and pupas collected in 2010 and one reference strain known as Rockefeller. The aqueous formulation of Bacillus thuringiensis var. israelensis (Bactivec, Labiofam, Cuba) was used. The bioassays complied with the World Health Organization guidelines for use of bacterial larvicides in the public health sector. The larval mortality was read after 24 hours and the results were processed by the statistical system SPSS (11.0) through Probit analysis. the evaluated mosquito strains showed high susceptibility to biolarvicide, there were no significant differences in LC50 values of Ae. aegypti strains, neither in the comparison of these values with those of the reference strain. the presented results indicate that the use of Bacillus thuringiensis var. israelensis continues to be a choice for the control of Aedes aegypti larval populations in La Habana province.

  7. Incorporating measurement error in n = 1 psychological autoregressive modeling

    Science.gov (United States)

    Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

    2015-01-01

    Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

  8. Characteristics of the transmission of autoregressive sub-patterns in financial time series

    Science.gov (United States)

    Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

    2014-09-01

    There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.

  9. Export Credit Insurances in Developing Countries: The Case of Turkey and IMT Countries

    Directory of Open Access Journals (Sweden)

    Cihat Koksal

    2018-05-01

    Full Text Available Export credit insurance is one of the substantial tools to promote export in a country. This paper endeavours to find out the effect of Export Credit Insurance covered by Export Credit Agencies on the developing countries’ export figures and GDP. The countries subject to the analysis are Turkey and Indonesia, Malaysia, Thailand also known as IMT Countries. The relationship between export value, economic growth and export credit insurances will be analyzed using Vector Autoregression (VAR Model.

  10. Interest-Rate Volatility in the Baltics: Issues of Measurement and International Contagion

    OpenAIRE

    Scott W. Hegerty

    2015-01-01

    Prior to their entry into the Eurozone, the Baltic countries of Estonia, Latvia, and Lithuania faced a major financial crisis that was brought about by events abroad. This financial risk led to instability in the real economy as well. This study uses monthly data to first model interest-rate volatility as a measure of financial instability before using our preferred volatility measure to test for international spillovers among interest-rate and output fluctuations. Vector Autoregressive (VAR)...

  11. What moves the primary stock and bond markets? Influence of macroeconomic factors on bond and equity issues in Malaysia and Korea

    OpenAIRE

    Ameer, Rashid

    2007-01-01

    This paper examines the impact of macroeconomic factors on the stock and bond market activities in two Asian countries. We examine the influence of interest rate changes, expected inflation rate, and stock market returns on aggregate stock and bond issuance in Malaysia and Korea. Using vector autoregressive models (VARs) and variance decomposition techniques, our result show that dynamics of equity and bond issuance in both countries vary significantly. Our findings show that there has been a...

  12. The Primary Sectors of the Economy and the Dutch Disease in Nigeria

    OpenAIRE

    J. O. Olusi; M. A. Olagunju

    2005-01-01

    This study examines whether the Dutch Disease—a resource boom leading to the decline of the erstwhile tradable sector—is present in Nigeria in the light of the rejection of the Dutch Disease thesis in other studies on Nigeria. Quarterly data for our variables of interest were predominantly sourced from the International Financial Statistics of the IMF. The data are analysed through the use of vector autoregressive (VAR) modelling consisting of impulse response functions and variance decomposi...

  13. Estimating core inflation : the role of oil price shocks and imported inflation

    OpenAIRE

    Bjørnland, Hilde Christiane

    1997-01-01

    This paper calculates core inflation, by imposing long run restrictions on a structural vector autoregression (VAR) model containing the growth rate of output, inflation and oil prices. Core inflation is identified as that component in inflation that has no long run effect on output. No restrictions are placed on the response of output and inflation to the oil price shocks. The analysis is applied to Norway and the United Kingdom, both oil producing OECD countries. A model that ...

  14. STUDYING THE IMPACT OF GOVERNMENT EXPENDITURES SHOCKS ON MACROECONOMIC VARIABLES OF THE IRANIAN ECONOMY

    Directory of Open Access Journals (Sweden)

    Ahmad Assadzadeh

    2013-07-01

    Full Text Available This paper studies impact of government expenditures shocks on Gross DomesticProduct (GDP, personal consumption, trade balanceand effective exchange rate.To the purpose, time series data of Iranian macroeconomic variables were usedcovering from 1976 to 2007. Vector autoregressive (VAR model, forecast errorvariance decomposition and momentary reaction functions were used in order tostudy the impact of government expenditures shockson macroeconomic variablesof Iranian economy. Extracted results from the estimate of VAR model andanalyses of forecast error variance decomposition showed that: positive shocks ofthe government expenditures increase GDP and personal consumption butdecrease trade balance. Impact of government expenditures positive shocksdecrease effective exchange rate only in first yearthen government expendituresshocks had positive but very little impact on effective exchange rate.

  15. Capital Market Integration in ASEAN Countries: Special Investigation of Indonesian Towards the Big Four

    Directory of Open Access Journals (Sweden)

    Barli Suryanta

    2012-01-01

    Full Text Available ASEAN already proposed financial integration through capital market integration based on ASEAN Economics Community (AEC 2020 treaty in order to aim comprehensive ASEAN economic integration. The objective of this study is to occur the capacity of Indonesian in terms of integrating its capital market towards the big four i.e., Singaporean, Malaysian, Philippines, and Thailand.  Vector Auto-regression (VAR analysis is utilized to investigate Indonesian market returns co-movement and dynamic link with ASEAN 4. The conclusion of this study, there is neither co-movement nor strong dynamic link between Indonesian capital market with those of Singaporean, Malaysian, Philippines, and Thailand. Keywords: ASEAN Capital market integration, Indonesian Capital Market, ASEAN 4 Capital Market, VAR Framework.

  16. Incorporating measurement error in n=1 psychological autoregressive modeling

    NARCIS (Netherlands)

    Schuurman, Noemi K.; Houtveen, Jan H.; Hamaker, Ellen L.

    2015-01-01

    Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive

  17. The Relevance of Political Stability on FDI: A VAR Analysis and ARDL Models for Selected Small, Developed, and Instability Threatened Economies

    Directory of Open Access Journals (Sweden)

    Petar Kurecic

    2017-06-01

    Full Text Available This paper studies the relevance of political stability on foreign direct investment (FDI and the relevance of FDI on economic growth, in three panels. The first panel contains 11 very small economies; the second contains five well-developed and politically stable economies with highly positive FDI net inflows, while the third is a panel with economies that are prone to political violence or targeted by the terrorist attacks. We employ a Granger causality test and implement a vector autoregressive (VAR framework within the panel setting. In order to test the sensitivity of the results and avoid robust errors, we employ an ARDL model for each of the countries within every panel. Based upon our results, we conclude that there is a long-term relationship between political stability and FDI for the panel of small economies, while we find no empiric evidence of such a relationship for both panels of larger and more developed economies. Similarly to the original hypothesis of Lucas (1990, we find that FDI outflows tend to go towards politically less stable countries. On the other hand, the empiric methodology employed did not find such conclusive evidence in the panels of politically more developed countries or in the small economies that this paper observes.

  18. A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching

    DEFF Research Database (Denmark)

    Haldrup, Niels; Nielsen, Frank; Nielsen, Morten Ørregaard

    2007-01-01

    A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the regime states as well as the possibility of fractional cointegra- tion. The model is relevant in describing the price dynamics of electricity prices where the transmission of power is subject...... to occasional congestion periods. For a system of bilat- eral prices non-congestion means that electricity prices are identical whereas congestion makes prices depart. Hence, the joint price dynamics implies switching between essen- tially a univariate price process under non-congestion and a bivariate price...

  19. Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators.

    Science.gov (United States)

    Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Sallehuddin, Roselina

    2013-01-01

    Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

  20. Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

    Directory of Open Access Journals (Sweden)

    Razana Alwee

    2013-01-01

    Full Text Available Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR and autoregressive integrated moving average (ARIMA to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

  1. Measurement of the CP-violation parameter Re(var-epsilon '/var-epsilon)

    International Nuclear Information System (INIS)

    Gibbons, L.K.; Barker, A.R.; Briere, R.A.; Makoff, G.; Papadimitriou, V.; Patterson, J.R.; Schwingenheuer, B.; Somalwar, S.V.; Wah, Y.W.; Winstein, B.; Winston, R.; Woods, M.; Yamamoto, H.; Swallow, E.C.; Bock, G.J.; Coleman, R.; Enagonio, J.; Hsiung, Y.B.; Ramberg, E.; Stanfield, K.; Tschirhart, R.; Yamanaka, T.; Gollin, G.D.; Karlsson, M.; Okamitsu, J.K.; Debu, P.; Peyaud, B.; Turlay, R.; Vallage, B.

    1993-01-01

    A measurement of the CP-violation parameter Re(var-epsilon '/var-epsilon) has been made using the full E731 data set. We find Re(var-epsilon '/var-epsilon)=(7.4±5.2±2.9)x10 -4 where the first error is statistical and the second systematic

  2. The asymptotic and exact Fisher information matrices of a vector ARMA process

    NARCIS (Netherlands)

    Klein, A.; Melard, G.; Saidi, A.

    2008-01-01

    The exact Fisher information matrix of a Gaussian vector autoregressive-moving average (VARMA) process has been considered for a time series of length N in relation to the exact maximum likelihood estimation method. In this paper it is shown that the Gaussian exact Fisher information matrix

  3. Taxation and political stability

    OpenAIRE

    Mutascu, Mihai; Tiwari, Aviral; Estrada, Fernando

    2011-01-01

    The present study is, in particular, an attempt to test the relationship between tax level and political stability by using some economic control variables and to see the relationship among government effectiveness, corruption, and GDP. For the purpose, we used the Vector Autoregression (VAR) approach in the panel framework, using a country-level panel data from 59 countries for the period 2002 to 2008. The salient features of this model are: (a) simplicity is based on a limited number of ...

  4. Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes

    Directory of Open Access Journals (Sweden)

    W. Wang

    2005-01-01

    Full Text Available Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average models for seasonal streamflow series. However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity effect, a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.

  5. arXiv Observation of the $\\varXi^{-}_{b}\\to J/\\psi\\varLambda K^{-}$ decay

    CERN Document Server

    Aaij, Roel; Adinolfi, Marco; Ajaltouni, Ziad; Akar, Simon; Albrecht, Johannes; Alessio, Federico; Alexander, Michael; Ali, Suvayu; Alkhazov, Georgy; Alvarez Cartelle, Paula; Alves Jr, Antonio Augusto; Amato, Sandra; Amerio, Silvia; Amhis, Yasmine; An, Liupan; Anderlini, Lucio; Andreassi, Guido; Andreotti, Mirco; Andrews, Jason; Appleby, Robert; Archilli, Flavio; d'Argent, Philippe; Arnau Romeu, Joan; Artamonov, Alexander; Artuso, Marina; Aslanides, Elie; Auriemma, Giulio; Baalouch, Marouen; Babuschkin, Igor; Bachmann, Sebastian; Back, John; Badalov, Alexey; Baesso, Clarissa; Baker, Sophie; Balagura, Vladislav; Baldini, Wander; Barlow, Roger; Barschel, Colin; Barsuk, Sergey; Barter, William; Baryshnikov, Fedor; Baszczyk, Mateusz; Batozskaya, Varvara; Batsukh, Baasansuren; Battista, Vincenzo; Bay, Aurelio; Beaucourt, Leo; Beddow, John; Bedeschi, Franco; Bediaga, Ignacio; Bel, Lennaert; Bellee, Violaine; Belloli, Nicoletta; Belous, Konstantin; Belyaev, Ivan; Ben-Haim, Eli; Bencivenni, Giovanni; Benson, Sean; Berezhnoy, Alexander; Bernet, Roland; Bertolin, Alessandro; Betancourt, Christopher; Betti, Federico; Bettler, Marc-Olivier; van Beuzekom, Martinus; Bezshyiko, Iaroslava; Bifani, Simone; Billoir, Pierre; Bird, Thomas; Birnkraut, Alex; Bitadze, Alexander; Bizzeti, Andrea; Blake, Thomas; Blanc, Frederic; Blouw, Johan; Blusk, Steven; Bocci, Valerio; Boettcher, Thomas; Bondar, Alexander; Bondar, Nikolay; Bonivento, Walter; Bordyuzhin, Igor; Borgheresi, Alessio; Borghi, Silvia; Borisyak, Maxim; Borsato, Martino; Bossu, Francesco; Boubdir, Meriem; Bowcock, Themistocles; Bowen, Espen Eie; Bozzi, Concezio; Braun, Svende; Britsch, Markward; Britton, Thomas; Brodzicka, Jolanta; Buchanan, Emma; Burr, Christopher; Bursche, Albert; Buytaert, Jan; Cadeddu, Sandro; Calabrese, Roberto; Calvi, Marta; Calvo Gomez, Miriam; Camboni, Alessandro; Campana, Pierluigi; Campora Perez, Daniel Hugo; Capriotti, Lorenzo; Carbone, Angelo; Carboni, Giovanni; Cardinale, Roberta; Cardini, Alessandro; Carniti, Paolo; Carson, Laurence; Carvalho Akiba, Kazuyoshi; Casse, Gianluigi; Cassina, Lorenzo; Castillo Garcia, Lucia; Cattaneo, Marco; Cavallero, Giovanni; Cenci, Riccardo; Chamont, David; Charles, Matthew; Charpentier, Philippe; Chatzikonstantinidis, Georgios; Chefdeville, Maximilien; Chen, Shanzhen; Cheung, Shu-Faye; Chobanova, Veronika; Chrzaszcz, Marcin; Cid Vidal, Xabier; Ciezarek, Gregory; Clarke, Peter; Clemencic, Marco; Cliff, Harry; Closier, Joel; Coco, Victor; Cogan, Julien; Cogneras, Eric; Cogoni, Violetta; Cojocariu, Lucian; Collazuol, Gianmaria; Collins, Paula; Comerma-Montells, Albert; Contu, Andrea; Cook, Andrew; Coombs, George; Coquereau, Samuel; Corti, Gloria; Corvo, Marco; Costa Sobral, Cayo Mar; Couturier, Benjamin; Cowan, Greig; Craik, Daniel Charles; Crocombe, Andrew; Cruz Torres, Melissa Maria; Cunliffe, Samuel; Currie, Robert; D'Ambrosio, Carmelo; Da Cunha Marinho, Franciole; Dall'Occo, Elena; Dalseno, Jeremy; David, Pieter; Davis, Adam; De Bruyn, Kristof; De Capua, Stefano; De Cian, Michel; De Miranda, Jussara; De Paula, Leandro; De Serio, Marilisa; De Simone, Patrizia; Dean, Cameron Thomas; Decamp, Daniel; Deckenhoff, Mirko; Del Buono, Luigi; Demmer, Moritz; Dendek, Adam; Derkach, Denis; Deschamps, Olivier; Dettori, Francesco; Dey, Biplab; Di Canto, Angelo; Dijkstra, Hans; Dordei, Francesca; Dorigo, Mirco; Dosil Suárez, Alvaro; Dovbnya, Anatoliy; Dreimanis, Karlis; Dufour, Laurent; Dujany, Giulio; Dungs, Kevin; Durante, Paolo; Dzhelyadin, Rustem; Dziurda, Agnieszka; Dzyuba, Alexey; Déléage, Nicolas; Easo, Sajan; Ebert, Marcus; Egede, Ulrik; Egorychev, Victor; Eidelman, Semen; Eisenhardt, Stephan; Eitschberger, Ulrich; Ekelhof, Robert; Eklund, Lars; Ely, Scott; Esen, Sevda; Evans, Hannah Mary; Evans, Timothy; Falabella, Antonio; Farley, Nathanael; Farry, Stephen; Fay, Robert; Fazzini, Davide; Ferguson, Dianne; Fernandez Prieto, Antonio; Ferrari, Fabio; Ferreira Rodrigues, Fernando; Ferro-Luzzi, Massimiliano; Filippov, Sergey; Fini, Rosa Anna; Fiore, Marco; Fiorini, Massimiliano; Firlej, Miroslaw; Fitzpatrick, Conor; Fiutowski, Tomasz; Fleuret, Frederic; Fohl, Klaus; Fontana, Marianna; Fontanelli, Flavio; Forshaw, Dean Charles; Forty, Roger; Franco Lima, Vinicius; Frank, Markus; Frei, Christoph; Fu, Jinlin; Funk, Wolfgang; Furfaro, Emiliano; Färber, Christian; Gallas Torreira, Abraham; Galli, Domenico; Gallorini, Stefano; Gambetta, Silvia; Gandelman, Miriam; Gandini, Paolo; Gao, Yuanning; Garcia Martin, Luis Miguel; García Pardiñas, Julián; Garra Tico, Jordi; Garrido, Lluis; Garsed, Philip John; Gascon, David; Gaspar, Clara; Gavardi, Laura; Gazzoni, Giulio; Gerick, David; Gersabeck, Evelina; Gersabeck, Marco; Gershon, Timothy; Ghez, Philippe; Gianì, Sebastiana; Gibson, Valerie; Girard, Olivier Göran; Giubega, Lavinia-Helena; Gizdov, Konstantin; Gligorov, Vladimir; Golubkov, Dmitry; Golutvin, Andrey; Gomes, Alvaro; Gorelov, Igor Vladimirovich; Gotti, Claudio; Graciani Diaz, Ricardo; Granado Cardoso, Luis Alberto; Graugés, Eugeni; Graverini, Elena; Graziani, Giacomo; Grecu, Alexandru; Griffith, Peter; Grillo, Lucia; Gruberg Cazon, Barak Raimond; Grünberg, Oliver; Gushchin, Evgeny; Guz, Yury; Gys, Thierry; Göbel, Carla; Hadavizadeh, Thomas; Hadjivasiliou, Christos; Haefeli, Guido; Haen, Christophe; Haines, Susan; Hamilton, Brian; Han, Xiaoxue; Hansmann-Menzemer, Stephanie; Harnew, Neville; Harnew, Samuel; Harrison, Jonathan; Hatch, Mark; He, Jibo; Head, Timothy; Heister, Arno; Hennessy, Karol; Henrard, Pierre; Henry, Louis; van Herwijnen, Eric; Heß, Miriam; Hicheur, Adlène; Hill, Donal; Hombach, Christoph; Hopchev, P H; Hulsbergen, Wouter; Humair, Thibaud; Hushchyn, Mikhail; Hutchcroft, David; Idzik, Marek; Ilten, Philip; Jacobsson, Richard; Jaeger, Andreas; Jalocha, Pawel; Jans, Eddy; Jawahery, Abolhassan; Jiang, Feng; John, Malcolm; Johnson, Daniel; Jones, Christopher; Joram, Christian; Jost, Beat; Jurik, Nathan; Kandybei, Sergii; Karacson, Matthias; Kariuki, James Mwangi; Karodia, Sarah; Kecke, Matthieu; Kelsey, Matthew; Kenzie, Matthew; Ketel, Tjeerd; Khairullin, Egor; Khanji, Basem; Khurewathanakul, Chitsanu; Kirn, Thomas; Klaver, Suzanne; Klimaszewski, Konrad; Koliiev, Serhii; Kolpin, Michael; Komarov, Ilya; Koopman, Rose; Koppenburg, Patrick; Kosmyntseva, Alena; Kozachuk, Anastasiia; Kozeiha, Mohamad; Kravchuk, Leonid; Kreplin, Katharina; Kreps, Michal; Krokovny, Pavel; Kruse, Florian; Krzemien, Wojciech; Kucewicz, Wojciech; Kucharczyk, Marcin; Kudryavtsev, Vasily; Kuonen, Axel Kevin; Kurek, Krzysztof; Kvaratskheliya, Tengiz; Lacarrere, Daniel; Lafferty, George; Lai, Adriano; Lanfranchi, Gaia; Langenbruch, Christoph; Latham, Thomas; Lazzeroni, Cristina; Le Gac, Renaud; van Leerdam, Jeroen; Leflat, Alexander; Lefrançois, Jacques; Lefèvre, Regis; Lemaitre, Florian; Lemos Cid, Edgar; Leroy, Olivier; Lesiak, Tadeusz; Leverington, Blake; Li, Tenglin; Li, Yiming; Likhomanenko, Tatiana; Lindner, Rolf; Linn, Christian; Lionetto, Federica; Liu, Xuesong; Loh, David; Longstaff, Iain; Lopes, Jose; Lucchesi, Donatella; Lucio Martinez, Miriam; Luo, Haofei; Lupato, Anna; Luppi, Eleonora; Lupton, Oliver; Lusiani, Alberto; Lyu, Xiao-Rui; Machefert, Frederic; Maciuc, Florin; Maev, Oleg; Maguire, Kevin; Malde, Sneha; Malinin, Alexander; Maltsev, Timofei; Manca, Giulia; Mancinelli, Giampiero; Manning, Peter Michael; Maratas, Jan; Marchand, Jean François; Marconi, Umberto; Marin Benito, Carla; Marinangeli, Matthieu; Marino, Pietro; Marks, Jörg; Martellotti, Giuseppe; Martin, Morgan; Martinelli, Maurizio; Martinez Santos, Diego; Martinez Vidal, Fernando; Martins Tostes, Danielle; Massacrier, Laure Marie; Massafferri, André; Matev, Rosen; Mathad, Abhijit; Mathe, Zoltan; Matteuzzi, Clara; Mauri, Andrea; Maurice, Emilie; Maurin, Brice; Mazurov, Alexander; McCann, Michael; McNab, Andrew; McNulty, Ronan; Meadows, Brian; Meier, Frank; Meissner, Marco; Melnychuk, Dmytro; Merk, Marcel; Merli, Andrea; Michielin, Emanuele; Milanes, Diego Alejandro; Minard, Marie-Noelle; Mitzel, Dominik Stefan; Mogini, Andrea; Molina Rodriguez, Josue; Monroy, Ignacio Alberto; Monteil, Stephane; Morandin, Mauro; Morawski, Piotr; Mordà, Alessandro; Morello, Michael Joseph; Morgunova, Olga; Moron, Jakub; Morris, Adam Benjamin; Mountain, Raymond; Muheim, Franz; Mulder, Mick; Mussini, Manuel; Müller, Dominik; Müller, Janine; Müller, Katharina; Müller, Vanessa; Naik, Paras; Nakada, Tatsuya; Nandakumar, Raja; Nandi, Anita; Nasteva, Irina; Needham, Matthew; Neri, Nicola; Neubert, Sebastian; Neufeld, Niko; Neuner, Max; Nguyen, Thi Dung; Nguyen-Mau, Chung; Nieswand, Simon; Niet, Ramon; Nikitin, Nikolay; Nikodem, Thomas; Nogay, Alla; Novoselov, Alexey; O'Hanlon, Daniel Patrick; Oblakowska-Mucha, Agnieszka; Obraztsov, Vladimir; Ogilvy, Stephen; Oldeman, Rudolf; Onderwater, Gerco; Otalora Goicochea, Juan Martin; Otto, Adam; Owen, Patrick; Oyanguren, Maria Aranzazu; Pais, Preema Rennee; Palano, Antimo; Palombo, Fernando; Palutan, Matteo; Papanestis, Antonios; Pappagallo, Marco; Pappalardo, Luciano; Parker, William; Parkes, Christopher; Passaleva, Giovanni; Pastore, Alessandra; Patel, Girish; Patel, Mitesh; Patrignani, Claudia; Pearce, Alex; Pellegrino, Antonio; Penso, Gianni; Pepe Altarelli, Monica; Perazzini, Stefano; Perret, Pascal; Pescatore, Luca; Petridis, Konstantinos; Petrolini, Alessandro; Petrov, Aleksandr; Petruzzo, Marco; Picatoste Olloqui, Eduardo; Pietrzyk, Boleslaw; Pikies, Malgorzata; Pinci, Davide; Pistone, Alessandro; Piucci, Alessio; Placinta, Vlad-Mihai; Playfer, Stephen; Plo Casasus, Maximo; Poikela, Tuomas; Polci, Francesco; Poluektov, Anton; Polyakov, Ivan; Polycarpo, Erica; Pomery, Gabriela Johanna; Popov, Alexander; Popov, Dmitry; Popovici, Bogdan; Poslavskii, Stanislav; Potterat, Cédric; Price, Eugenia; Price, Joseph David; Prisciandaro, Jessica; Pritchard, Adrian; Prouve, Claire; Pugatch, Valery; Puig Navarro, Albert; Punzi, Giovanni; Qian, Wenbin; Quagliani, Renato; Rachwal, Bartolomiej; Rademacker, Jonas; Rama, Matteo; Ramos Pernas, Miguel; Rangel, Murilo; Raniuk, Iurii; Ratnikov, Fedor; Raven, Gerhard; Redi, Federico; Reichert, Stefanie; dos Reis, Alberto; Remon Alepuz, Clara; Renaudin, Victor; Ricciardi, Stefania; Richards, Sophie; Rihl, Mariana; Rinnert, Kurt; Rives Molina, Vicente; Robbe, Patrick; Rodrigues, Ana Barbara; Rodrigues, Eduardo; Rodriguez Lopez, Jairo Alexis; Rodriguez Perez, Pablo; Rogozhnikov, Alexey; Roiser, Stefan; Rollings, Alexandra Paige; Romanovskiy, Vladimir; Romero Vidal, Antonio; Ronayne, John William; Rotondo, Marcello; Rudolph, Matthew Scott; Ruf, Thomas; Ruiz Valls, Pablo; Saborido Silva, Juan Jose; Sadykhov, Elnur; Sagidova, Naylya; Saitta, Biagio; Salustino Guimaraes, Valdir; Sanchez Mayordomo, Carlos; Sanmartin Sedes, Brais; Santacesaria, Roberta; Santamarina Rios, Cibran; Santimaria, Marco; Santovetti, Emanuele; Sarti, Alessio; Satriano, Celestina; Satta, Alessia; Saunders, Daniel Martin; Savrina, Darya; Schael, Stefan; Schellenberg, Margarete; Schiller, Manuel; Schindler, Heinrich; Schlupp, Maximilian; Schmelling, Michael; Schmelzer, Timon; Schmidt, Burkhard; Schneider, Olivier; Schopper, Andreas; Schubert, Konstantin; Schubiger, Maxime; Schune, Marie Helene; Schwemmer, Rainer; Sciascia, Barbara; Sciubba, Adalberto; Semennikov, Alexander; Sergi, Antonino; Serra, Nicola; Serrano, Justine; Sestini, Lorenzo; Seyfert, Paul; Shapkin, Mikhail; Shapoval, Illya; Shcheglov, Yury; Shears, Tara; Shekhtman, Lev; Shevchenko, Vladimir; Siddi, Benedetto Gianluca; Silva Coutinho, Rafael; Silva de Oliveira, Luiz Gustavo; Simi, Gabriele; Simone, Saverio; Sirendi, Marek; Skidmore, Nicola; Skwarnicki, Tomasz; Smith, Eluned; Smith, Iwan Thomas; Smith, Jackson; Smith, Mark; Snoek, Hella; Soares Lavra, Lais; Sokoloff, Michael; Soler, Paul; Souza De Paula, Bruno; Spaan, Bernhard; Spradlin, Patrick; Sridharan, Srikanth; Stagni, Federico; Stahl, Marian; Stahl, Sascha; Stefko, Pavol; Stefkova, Slavorima; Steinkamp, Olaf; Stemmle, Simon; Stenyakin, Oleg; Stevens, Holger; Stevenson, Scott; Stoica, Sabin; Stone, Sheldon; Storaci, Barbara; Stracka, Simone; Straticiuc, Mihai; Straumann, Ulrich; Sun, Liang; Sutcliffe, William; Swientek, Krzysztof; Syropoulos, Vasileios; Szczekowski, Marek; Szumlak, Tomasz; T'Jampens, Stephane; Tayduganov, Andrey; Tekampe, Tobias; Tellarini, Giulia; Teubert, Frederic; Thomas, Eric; van Tilburg, Jeroen; Tilley, Matthew James; Tisserand, Vincent; Tobin, Mark; Tolk, Siim; Tomassetti, Luca; Tonelli, Diego; Topp-Joergensen, Stig; Toriello, Francis; Tournefier, Edwige; Tourneur, Stephane; Trabelsi, Karim; Traill, Murdo; Tran, Minh Tâm; Tresch, Marco; Trisovic, Ana; Tsaregorodtsev, Andrei; Tsopelas, Panagiotis; Tully, Alison; Tuning, Niels; Ukleja, Artur; Ustyuzhanin, Andrey; Uwer, Ulrich; Vacca, Claudia; Vagnoni, Vincenzo; Valassi, Andrea; Valat, Sebastien; Valenti, Giovanni; Vazquez Gomez, Ricardo; Vazquez Regueiro, Pablo; Vecchi, Stefania; van Veghel, Maarten; Velthuis, Jaap; Veltri, Michele; Veneziano, Giovanni; Venkateswaran, Aravindhan; Vernet, Maxime; Vesterinen, Mika; Viana Barbosa, Joao Vitor; Viaud, Benoit; Vieira, Daniel; Vieites Diaz, Maria; Viemann, Harald; Vilasis-Cardona, Xavier; Vitti, Marcela; Volkov, Vladimir; Vollhardt, Achim; Voneki, Balazs; Vorobyev, Alexey; Vorobyev, Vitaly; Voß, Christian; de Vries, Jacco; Vázquez Sierra, Carlos; Waldi, Roland; Wallace, Charlotte; Wallace, Ronan; Walsh, John; Wang, Jianchun; Ward, David; Wark, Heather Mckenzie; Watson, Nigel; Websdale, David; Weiden, Andreas; Whitehead, Mark; Wicht, Jean; Wilkinson, Guy; Wilkinson, Michael; Williams, Mark Richard James; Williams, Matthew; Williams, Mike; Williams, Timothy; Wilson, Fergus; Wimberley, Jack; Wishahi, Julian; Wislicki, Wojciech; Witek, Mariusz; Wormser, Guy; Wotton, Stephen; Wraight, Kenneth; Wyllie, Kenneth; Xie, Yuehong; Xing, Zhou; Xu, Zhirui; Yang, Zhenwei; Yao, Yuezhe; Yin, Hang; Yu, Jiesheng; Yuan, Xuhao; Yushchenko, Oleg; Zarebski, Kristian Alexander; Zavertyaev, Mikhail; Zhang, Liming; Zhang, Yanxi; Zhang, Yu; Zhelezov, Alexey; Zheng, Yangheng; Zhu, Xianglei; Zhukov, Valery; Zucchelli, Stefano

    2017-09-10

    The observation of the decay $\\varXi_{b}^{-}\\to J/\\psi\\varLambda K^{-}$ is reported, using a data sample corresponding to an integrated luminosity of $3~\\mathrm{fb}^{-1}$, collected by the LHCb detector in $pp$ collisions at centre-of-mass energies of $7$ and $8~\\mathrm{TeV}$. The production rate of $\\varXi_{b}^{-}$ baryons detected in the decay $\\varXi_{b}^{-}\\to J/\\psi\\varLambda K^{-}$ is measured relative to that of $\\varLambda_{b}^{0}$ baryons using the decay $\\varLambda_{b}^{0}\\to J/\\psi \\varLambda$. Integrated over the $b$-baryon transverse momentum $p_{\\rm T}<25~\\mathrm{GeV/}c $ and rapidity $2.0 < y < 4.5$, the measured ratio is \\begin{equation*} \\frac{f_{\\varXi_{b}^{-}}}{f_{\\varLambda_{b}^{0}}}\\frac{\\mathcal{B}(\\varXi_{b}^{-}\\to J/\\psi\\varLambda K^{-})}{\\mathcal{B}(\\varLambda_{b}^{0}\\to J/\\psi \\varLambda)}=(4.19\\pm 0.29~(\\mathrm{stat})\\pm0.14~(\\mathrm{syst}))\\times 10^{-2}, \\end{equation*}where $f_{\\varXi_{b}^{-}}$ and $f_{\\varLambda_{b}^{0}}$ are the fragmentation fractions of $b\\to\\varXi_{...

  6. ACCOUNTING INNOVATION ANALYSIS FOR THE STOCK PRICES AND MACROECONOMIC FACTORS OF FIVE ASEAN COUNTRIES DURING AND POST THE 1997 ASIAN FINANCIAL CRISIS

    Directory of Open Access Journals (Sweden)

    Adwin Surja Atmadja

    2004-01-01

    Full Text Available This paper seeks to examine some of the dynamic interactions of stock prices and macroeconomic factors in five ASEAN countries, Indonesia; Malaysia; the Philippines; Singapore; and Thailand with particular attention to the 1997 Asian financial crisis and period onwards. Using monthly time series data of the countries, accounting innovation analyses based on vector autoregressive (VAR analytical framework is employed to empirically examine the interaction among the variables. This research reveals that, firstly, a shock to a particular variable in the model results in various contemporaneous reactions by other variables across the countries during the sample period. Secondly, the general forecast error variance decomposition results likely reinforce the outcomes of the general impulse response analyses in most of the countries. Abstract in Bahasa Indonesia : Makalah ini ditujukan untuk mengkaji berbagai interaksi dinamik yang terjadi antara indeks harga saham dan factor-faktor ekonomi makro di kelima negara-negara ASEAN, yaitu Indonesia; Malaysia; Filipina; Singapura; dan Thailand pada saat dan setelah berlangsungnya krisis keuangan Asia tahun 1997. Dengan menggunakan data time series bulanan dari negara-negara tersebut, accounting innovation analysis yang didasarkan atas kerangka analisa vector autoregressive (VAR diaplikasikan untuk menguji secara empiris interaksi dinamik antara berbagai variabel tersebut. Penelitian ini mengungkapkan bahwa, pertama, suatu goncangan terhadap suatu variabel tertentu di dalam model menghasilkan berbagai reaksi temporer oleh variabel-variabel lainnya di seluruh negara-negara tersebut selama periode penelitian. Kedua, hasil-hasil analisa general forecast error variance decomposition nampaknya cenderung memperkuat hasil-hasil dari analisa general impulse response di sebagian besar negara-negara ASEAN tersebut. Kata kunci: analisa accounting innovation, krisis keuangan Asia, pasar modal, faktor-faktor ekonomi makro

  7. Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

    CSIR Research Space (South Africa)

    Das, Sonali

    2010-01-01

    Full Text Available and Gertler, 1995), but also because changes in house prices tend to have important wealth effects on consumption (International Monetary Fund, 2000) and investment (Topel and Rosen, 1988), the importance of forecasting house price infl ation is vital, since... sections, respectively, lay out the DFM and outline the basics of the VAR, the Minnesota-type BVARs, and the SBVARs based on the fi rst-order spatial contiguity (FOSC) and the random walk averaging (RWA) priors developed by LeSage and Pan (1995) and Le...

  8. Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China.

    Science.gov (United States)

    Zhang, Yong; Zhong, Miner; Geng, Nana; Jiang, Yunjian

    2017-01-01

    The market demand for electric vehicles (EVs) has increased in recent years. Suitable models are necessary to understand and forecast EV sales. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The EV sales in China, which are categorized into battery and plug-in EVs, are predicted in both short term (up to December 2017) and long term (up to 2020), as statistical proofs of the growth of the Chinese EV industry.

  9. Three essays on price dynamics and causations among energy markets and macroeconomic information

    Science.gov (United States)

    Hong, Sung Wook

    This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

  10. A complex autoregressive model and application to monthly temperature forecasts

    Directory of Open Access Journals (Sweden)

    X. Gu

    2005-11-01

    Full Text Available A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventional statistical models, in predicting monthly temperature anomalies in July at 160 meteorological stations in mainland China. The conventional statistical models include an autoregressive model, where the real number and the imaginary number are separately disposed, an autoregressive model in the real number domain, and a persistence-forecast model.

  11. Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity

    Directory of Open Access Journals (Sweden)

    Isao Ishida

    2015-01-01

    Full Text Available We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500 and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.

  12. Information contraction and extraction by multivariate autoregressive (MAR) modelling. Pt. 2. Dominant noise sources in BWRS

    International Nuclear Information System (INIS)

    Morishima, N.

    1996-01-01

    The multivariate autoregressive (MAR) modeling of a vector noise process is discussed in terms of the estimation of dominant noise sources in BWRs. The discussion is based on a physical approach: a transfer function model on BWR core dynamics is utilized in developing a noise model; a set of input-output relations between three system variables and twelve different noise sources is obtained. By the least-square fitting of a theoretical PSD on neutron noise to an experimental one, four kinds of dominant noise sources are selected. It is shown that some of dominant noise sources consist of two or more different noise sources and have the spectral properties of being coloured and correlated with each other. By diagonalizing the PSD matrix for dominant noise sources, we may obtain an MAR expression for a vector noise process as a response to the diagonal elements(i.e. residual noises) being white and mutually-independent. (Author)

  13. The dynamic correlation between policy uncertainty and stock market returns in China

    Science.gov (United States)

    Yang, Miao; Jiang, Zhi-Qiang

    2016-11-01

    The dynamic correlation is examined between government's policy uncertainty and Chinese stock market returns in the period from January 1995 to December 2014. We find that the stock market is significantly correlated to policy uncertainty based on the results of the Vector Auto Regression (VAR) and Structural Vector Auto Regression (SVAR) models. In contrast, the results of the Dynamic Conditional Correlation Generalized Multivariate Autoregressive Conditional Heteroscedasticity (DCC-MGARCH) model surprisingly show a low dynamic correlation coefficient between policy uncertainty and market returns, suggesting that the fluctuations of each variable are greatly influenced by their values in the preceding period. Our analysis highlights the understanding of the dynamical relationship between stock market and fiscal and monetary policy.

  14. THE ALLOMETRIC-AUTOREGRESSIVE MODEL IN GENETIC ...

    African Journals Online (AJOL)

    The application of an allometric-autoregressive model for the quantification of growth and efficiency of feed utilization for purposes of selection for ... be of value in genetic studies. ... mass) gives a fair indication of the cumulative preweaning.

  15. Kalman Filter or VAR Models to Predict Unemployment Rate in Romania?

    Directory of Open Access Journals (Sweden)

    Simionescu Mihaela

    2015-06-01

    Full Text Available This paper brings to light an economic problem that frequently appears in practice: For the same variable, more alternative forecasts are proposed, yet the decision-making process requires the use of a single prediction. Therefore, a forecast assessment is necessary to select the best prediction. The aim of this research is to propose some strategies for improving the unemployment rate forecast in Romania by conducting a comparative accuracy analysis of unemployment rate forecasts based on two quantitative methods: Kalman filter and vector-auto-regressive (VAR models. The first method considers the evolution of unemployment components, while the VAR model takes into account the interdependencies between the unemployment rate and the inflation rate. According to the Granger causality test, the inflation rate in the first difference is a cause of the unemployment rate in the first difference, these data sets being stationary. For the unemployment rate forecasts for 2010-2012 in Romania, the VAR models (in all variants of VAR simulations determined more accurate predictions than Kalman filter based on two state space models for all accuracy measures. According to mean absolute scaled error, the dynamic-stochastic simulations used in predicting unemployment based on the VAR model are the most accurate. Another strategy for improving the initial forecasts based on the Kalman filter used the adjusted unemployment data transformed by the application of the Hodrick-Prescott filter. However, the use of VAR models rather than different variants of the Kalman filter methods remains the best strategy in improving the quality of the unemployment rate forecast in Romania. The explanation of these results is related to the fact that the interaction of unemployment with inflation provides useful information for predictions of the evolution of unemployment related to its components (i.e., natural unemployment and cyclical component.

  16. Linking Simple Economic Theory Models and the Cointegrated Vector AutoRegressive Model

    DEFF Research Database (Denmark)

    Møller, Niels Framroze

    This paper attempts to clarify the connection between simple economic theory models and the approach of the Cointegrated Vector-Auto-Regressive model (CVAR). By considering (stylized) examples of simple static equilibrium models, it is illustrated in detail, how the theoretical model and its stru....... Further fundamental extensions and advances to more sophisticated theory models, such as those related to dynamics and expectations (in the structural relations) are left for future papers......This paper attempts to clarify the connection between simple economic theory models and the approach of the Cointegrated Vector-Auto-Regressive model (CVAR). By considering (stylized) examples of simple static equilibrium models, it is illustrated in detail, how the theoretical model and its......, it is demonstrated how other controversial hypotheses such as Rational Expectations can be formulated directly as restrictions on the CVAR-parameters. A simple example of a "Neoclassical synthetic" AS-AD model is also formulated. Finally, the partial- general equilibrium distinction is related to the CVAR as well...

  17. Correlation-constrained and sparsity-controlled vector autoregressive model for spatio-temporal wind power forecasting

    DEFF Research Database (Denmark)

    Zhao, Yongning; Ye, Lin; Pinson, Pierre

    2018-01-01

    The ever-increasing number of wind farms has brought both challenges and opportunities in the development of wind power forecasting techniques to take advantage of interdependenciesbetweentensorhundredsofspatiallydistributedwind farms, e.g., over a region. In this paper, a Sparsity-Controlled Vec......The ever-increasing number of wind farms has brought both challenges and opportunities in the development of wind power forecasting techniques to take advantage of interdependenciesbetweentensorhundredsofspatiallydistributedwind farms, e.g., over a region. In this paper, a Sparsity...... matrices in direct manner. However this original SC-VAR is difficult to implement due to its complicated constraints and the lack of guidelines for setting its parameters. To reduce the complexity of this MINLP and to make it possible to incorporate prior expert knowledge to benefit model building...

  18. Stable Parameter Estimation for Autoregressive Equations with Random Coefficients

    Directory of Open Access Journals (Sweden)

    V. B. Goryainov

    2014-01-01

    Full Text Available In recent yearsthere has been a growing interest in non-linear time series models. They are more flexible than traditional linear models and allow more adequate description of real data. Among these models a autoregressive model with random coefficients plays an important role. It is widely used in various fields of science and technology, for example, in physics, biology, economics and finance. The model parameters are the mean values of autoregressive coefficients. Their evaluation is the main task of model identification. The basic method of estimation is still the least squares method, which gives good results for Gaussian time series, but it is quite sensitive to even small disturbancesin the assumption of Gaussian observations. In this paper we propose estimates, which generalize the least squares estimate in the sense that the quadratic objective function is replaced by an arbitrary convex and even function. Reasonable choice of objective function allows you to keep the benefits of the least squares estimate and eliminate its shortcomings. In particular, you can make it so that they will be almost as effective as the least squares estimate in the Gaussian case, but almost never loose in accuracy with small deviations of the probability distribution of the observations from the Gaussian distribution.The main result is the proof of consistency and asymptotic normality of the proposed estimates in the particular case of the one-parameter model describing the stationary process with finite variance. Another important result is the finding of the asymptotic relative efficiency of the proposed estimates in relation to the least squares estimate. This allows you to compare the two estimates, depending on the probability distribution of innovation process and of autoregressive coefficients. The results can be used to identify an autoregressive process, especially with nonGaussian nature, and/or of autoregressive processes observed with gross

  19. The Asymmetric Effects of Oil Price Changes on the Economic Activities in Indonesia

    OpenAIRE

    Rina Juliet Artami; Yonosuke Hara

    2018-01-01

    This paper analyzes the asymmetric impact of oil price changes on the economic growth of and inflation in Indonesia by using the vector autoregression (VAR) model for the period from 1990Q1 to 2016Q4. The results show that the impact of oil price changes on the gross domestic product (GDP) is asymmetric, as a drop in oil prices decreases the GDP, whereas an increase in oil prices does not significantly affect GDP. It is crucial for Indonesia to reduce its dependency on oil, mainly as its prim...

  20. Forecasting Euro Area Inflation Using Single-Equation and Multivariate VAR–Models

    Directory of Open Access Journals (Sweden)

    Gerdesmeier Dieter

    2017-12-01

    Full Text Available Forecasting inflation is of key relevance for central banks, not least because the objective of low and stable inflation is embodied in most central banks’ mandates and the monetary policy transmission mechanism is well known to be subject to long and variable lags. To our best knowledge, central banks around the world use conditional as well as unconditional forecasts for such purposes. Turning to unconditional forecasts, these can be derived on the basis of structural and non-structural models. Among the latter, vector autoregressive (VAR-models are among the most popular tools.

  1. The causal nexus between oil prices and equity market in the U.S.: A regime switching model

    International Nuclear Information System (INIS)

    Balcilar, Mehmet; Ozdemir, Zeynel Abidin

    2013-01-01

    The aim of this paper is to analyse the causal link between monthly oil futures price changes and a sub-grouping of S and P 500 stock index changes. The causal linkage between oil and stock markets is modelled using a vector autoregressive model with time-varying parameters so as to reflect changes in Granger causality over time. A Markov switching vector autoregressive (MS-VAR) model, in which causal link between the series is stochastic and governed by an unobservable Markov chain, is used for inferring time-varying causality. Although we do not find any lead–lag type Granger causality, the results based on the MS-VAR model clearly show that oil futures price has strong regime prediction power for a sub-grouping of S and P 500 stock index during various sub-periods in the sample, while there is a weak evidence for the regime prediction power of a sub-grouping of S and P 500 stock indexes. The regime-prediction non-causality tests on the MS-VAR model show that both variables are useful for making inference about the regime process and that the evidence on regime-prediction causality is primarily found in the equation describing a sub-grouping of S and P 500 stock market returns. The evidence from the conditional non-causality tests shows that past information on the other series fails to improve the one step ahead prediction for both oil futures and stock returns. - Highlights: • We analyse the causal links between oil futures price and a sub-grouping of S and P 500 index. • The causal links are modelled using a regime switching model. • We do not find any lead–lag type Granger causality between the series. • The results show that oil futures price has regime prediction power for a sub-grouping of S and P 500 stock index

  2. Insecticidal effects of Ocimum sanctum var. cubensis essential oil on the diseases vector Chrysomya putoria

    Directory of Open Access Journals (Sweden)

    Idelsy Chil-Núñez

    2018-05-01

    Full Text Available Context: The blowfly Chrysomya putoria is widely distributed throughout the Neotropical region and, besides transmitting pathogens; they could cause secondary myiasis. Botanical insecticides provide an alternative to synthetic pesticides because the excessive use of synthetic insecticides resulted in a progressive resistance of the pests to these chemicals, diminishing their effectiveness and generating consequences with negative environmental impact. The essential oil extracted from Ocimum sanctum (basil has showed insecticidal activity against some insects but has no reported studies on the activity of this plant against flies. Aims: To evaluate the insecticidal effects of Ocimum sanctum var. cubensis Gomes essential oil on the post embryonic development of Chrysomya putoria. Methods: The colonies of Chrysomya putoria were established and maintained at the Laboratório de Entomologia Médica e Forense (FIOCRUZ, Rio de Janeiro, Brazil. The basil essential oil was tested in six concentrations (4.13, 8.25, 20.63, 41.25, 61.87 and 80,25 mg/mL. Mortality and changes in life cycle were recorded daily. Results: β-caryophyllene, β-selinene and eugenol, were the main constituents of the basil essential oil. The experiments demonstrated that in all concentrations tested, this essential oil shortening the duration of all post embryonic stages having a direct impact in the viability of this fly estimating the LC50 in 7.47 mg/mL of concentration. In addition, the essential oil caused morphological alterations in abdomen, wings and ptilinum at lower concentrations. Conclusions: This essential oil emerge as a good option for the control of the disease vector blowfly Chrysomya putoria.

  3. Pemodelan Markov Switching Autoregressive

    OpenAIRE

    Ariyani, Fiqria Devi; Warsito, Budi; Yasin, Hasbi

    2014-01-01

    Transition from depreciation to appreciation of exchange rate is one of regime switching that ignored by classic time series model, such as ARIMA, ARCH, or GARCH. Therefore, economic variables are modeled by Markov Switching Autoregressive (MSAR) which consider the regime switching. MLE is not applicable to parameters estimation because regime is an unobservable variable. So that filtering and smoothing process are applied to see the regime probabilities of observation. Using this model, tran...

  4. Integration of Stock Markets between Indonesia and Its Major Trading Partners

    Directory of Open Access Journals (Sweden)

    Bakri Abdul Karim

    2009-05-01

    Full Text Available Using Autoregressive Distributed Lag (ARDL and Vector Autoregressive (VAR frameworks, this study examines the integration between the emerging stock market of Indonesia and its major trading partners (i.e., Japan, the U.S., Singapore, and China. During the period of July 1998 to December 2007, the Indonesian stock market is found to be integrated with its major trading partners. Thus, this implies that there is a limited room available for investors to gain risk-reduction benefits through diversifying their portfolio in those markets. Meanwhile, in the short run, the Indonesian market responds more to shocks in the U.S. and Singapore than in Japan and China. In designing policies pertaining to its stock market, the Indonesian government should take into account any development in the stock markets of its major trading partners, particularly the U.S. and Singaporean markets.

  5. A THRESHOLD-VAR APPROACH TO ASSESS THE EFFICACY OF THE EU IMPORT REGIME

    Directory of Open Access Journals (Sweden)

    Fabio Gaetano Santeramo

    2014-01-01

    Full Text Available The efficacy of the entry price policy in the European fresh fruits and vegetables sector is not well understood. We investigate econometrically the efficacy of the import policy. The analysis estimates a threshold vector autoregressive model using data on imports the main competing country on the European Union domestic markets. Our results allow concluding on the insulating effects induced by the entry price system. We argue that the quota restrictions are likely to provide larger contribution to the domestic market stabilization. Policy implications are provided.

  6. Weinig VVT-instellingen met VAR : onderzoek naar VAR's in Nederland

    NARCIS (Netherlands)

    Corina de Feijter; Pieterbas Lalleman

    V&VN is op zoek gegaan naar alle actieve Verpleegkundige en/of Verzorgende Adviesraden (VAR) in Nederland. Het blijkt dat in totaal 144 zorginstellingen (24%) een VAR hebben. Vooral in de VVT-sector is het aantal VAR’s laag: 13%.

  7. Structural VAR analysis of monetary transmission mechanism and central bank’s response to equity volatility shock in Taiwan

    OpenAIRE

    Lo, Chi-Sheng

    2016-01-01

    This research applies recursive Structural Vector Auto Regression (SVAR) model with short-run restriction into two kinds of shocks: monetary and volatility. The first SVAR estimates the shock of contractionary monetary policy on Taiwan’s key monthly macroeconomic variables including exports, CPI, exchange rate, money supply, and Taiwan Weighted Stock Exchange (TWSE) Index. The second SVAR estimates the shock of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) volatility of TW...

  8. New var reconstruction algorithm exposes high var sequence diversity in a single geographic location in Mali.

    Science.gov (United States)

    Dara, Antoine; Drábek, Elliott F; Travassos, Mark A; Moser, Kara A; Delcher, Arthur L; Su, Qi; Hostelley, Timothy; Coulibaly, Drissa; Daou, Modibo; Dembele, Ahmadou; Diarra, Issa; Kone, Abdoulaye K; Kouriba, Bourema; Laurens, Matthew B; Niangaly, Amadou; Traore, Karim; Tolo, Youssouf; Fraser, Claire M; Thera, Mahamadou A; Djimde, Abdoulaye A; Doumbo, Ogobara K; Plowe, Christopher V; Silva, Joana C

    2017-03-28

    Encoded by the var gene family, highly variable Plasmodium falciparum erythrocyte membrane protein-1 (PfEMP1) proteins mediate tissue-specific cytoadherence of infected erythrocytes, resulting in immune evasion and severe malaria disease. Sequencing and assembling the 40-60 var gene complement for individual infections has been notoriously difficult, impeding molecular epidemiological studies and the assessment of particular var elements as subunit vaccine candidates. We developed and validated a novel algorithm, Exon-Targeted Hybrid Assembly (ETHA), to perform targeted assembly of var gene sequences, based on a combination of Pacific Biosciences and Illumina data. Using ETHA, we characterized the repertoire of var genes in 12 samples from uncomplicated malaria infections in children from a single Malian village and showed them to be as genetically diverse as vars from isolates from around the globe. The gene var2csa, a member of the var family associated with placental malaria pathogenesis, was present in each genome, as were vars previously associated with severe malaria. ETHA, a tool to discover novel var sequences from clinical samples, will aid the understanding of malaria pathogenesis and inform the design of malaria vaccines based on PfEMP1. ETHA is available at: https://sourceforge.net/projects/etha/ .

  9. Mathematical model with autoregressive process for electrocardiogram signals

    Science.gov (United States)

    Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

    2018-04-01

    The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

  10. on the performance of Autoregressive Moving Average Polynomial

    African Journals Online (AJOL)

    Timothy Ademakinwa

    Distributed Lag (PDL) model, Autoregressive Polynomial Distributed Lag ... Moving Average Polynomial Distributed Lag (ARMAPDL) model. ..... Global Journal of Mathematics and Statistics. Vol. 1. ... Business and Economic Research Center.

  11. Potential for wind extraction from 4D-Var assimilation of aerosols and moisture

    Science.gov (United States)

    Zaplotnik, Žiga; Žagar, Nedjeljka

    2017-04-01

    We discuss the potential of the four-dimensional variational data assimilation (4D-Var) to retrieve the unobserved wind field from observations of atmospheric tracers and the mass field through internal model dynamics and the multivariate relationships in the background-error term for 4D-Var. The presence of non-linear moist dynamics makes the wind retrieval from tracers very difficult. On the other hand, it has been shown that moisture observations strongly influence both tropical and mid-latitude wind field in 4D-Var. We present an intermediate complexity model that describes nonlinear interactions between the wind, temperature, aerosols and moisture including their sinks and sources in the framework of the so-called first baroclinic mode atmosphere envisaged by A. Gill. Aerosol physical processes, which are included in the model, are the non-linear advection, diffusion and sources and sinks that exist as dry and wet deposition and diffusion. Precipitation is parametrized according to the Betts-Miller scheme. The control vector for 4D-Var includes aerosols, moisture and the three dynamical variables. The former is analysed univariately whereas wind field and mass field are analysed in a multivariate fashion taking into account quasi-geostrophic and unbalanced dynamics. The OSSE type of studies are performed for the tropical region to assess the ability of 4D-Var to extract wind-field information from the time series of observations of tracers as a function of the flow nonlinearity, the observations density and the length of the assimilation window (12 hours and 24 hours), in dry and moist environment. Results show that the 4D-Var assimilation of aerosols and temperature data is beneficial for the wind analysis with analysis errors strongly dependent on the moist processes and reliable background-error covariances.

  12. Permanent and transitory oil volatility and aggregate investment in Malaysia

    International Nuclear Information System (INIS)

    Ibrahim, Mansor H.; Ahmed, Huson Joher Ali

    2014-01-01

    This paper investigates the relation between aggregate investment and oil volatility and its permanent and transitory components for a developing country, Malaysia. In the paper, the components generalized autoregressive conditional heteroskedasticity (CGARCH) model is utilized to decompose conditional oil volatility into permanent oil volatility and transitory oil volatility. Respectively reflecting fundamental-driven and random shifts in oil volatility, they are expected to exert differential effects on aggregate investment. Adopting a vector autoregression (VAR) framework to allow feedback effects between aggregate investment and its determinants, the paper documents evidence supporting the adverse effects of conditional oil volatility, permanent oil volatility and transitory oil volatility on aggregate investment and real output. Interestingly, contrary to the findings for the developed markets (US and OECD), the real effects of permanent oil volatility tend to be stronger. These findings are reasonably robust to variable specification and measurements in the VAR system. Hence, there is an indication that heightened oil volatility accounts for the slumps in Malaysia's aggregate investment after the Asian financial crisis. - Highlights: • Examines the role of oil volatility in Malaysia's aggregate investment. • Makes distinction between permanent and temporary volatility using CGARCH. • Both volatility components depress investment. • Permanent volatility has larger adverse effects. • Results are robust to alternative model specifications

  13. Identification of BWR feedwater control system using autoregressive integrated model

    International Nuclear Information System (INIS)

    Kanemoto, Shigeru; Andoh, Yasumasa; Yamamoto, Fumiaki; Idesawa, Masato; Itoh, Kazuo.

    1983-01-01

    With the view of contributing toward more reliable interpretation of noise behavior under normal operating conditions, which is essential for correct detection and/or diagnosis of incipient anomalies in nuclear power plants by noise analysis technique, studies has been undertaken of the noise behavior in a BWR feedwater control system, with use made of a multivariate autoregressive modeling technique. Noise propagation mechanisms as well as open- and closed-loop responses in the system are identified from noise data by a method in which an autoregressive integrated model is introduced. The closed-loop responses obtained with this method are compared with transient data from an actual test, and confirmed to be reliable in estimating semi-quantitative features. Other analyses performed with this model also yield results that appear most reasonable in their physical characteristics. These results have demonstrated the effectiveness of the noise analyses technique based on the autoregressive integrated model for evaluating and diagnosing the performance of feedwater control systems. (author)

  14. Texture classification using autoregressive filtering

    Science.gov (United States)

    Lawton, W. M.; Lee, M.

    1984-01-01

    A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

  15. Delice(Olea europea var. oleaster L.) ile zeytin (Olea europea var.sativa) arasında anatomik ve palinojik ayrıcalıklar (The Anatomic And Palynological Differences Between Olea europea var. oleaster L. AND Olea europea var.sativa)

    OpenAIRE

    Kaya, Zafer

    1991-01-01

    Delice(Olea europea var. oleaster L.) ile zeytin (Olea europea var.sativa) arasında anatomik ve palinojik ayrıcalıklar (The Anatomic And Palynological Differences Between Olea europea var. oleaster L. AND Olea europea var.sativa)

  16. Recent oil price shock and Tunisian economy

    International Nuclear Information System (INIS)

    Jbir, Rafik; Zouari-Ghorbel, Sonia

    2009-01-01

    The objective of this paper is to study the oil prices-macroeconomy relationship by the analysis of the role of subsidy policy. The vector autoregression (VAR) method was employed to analyze the data over the period 1993 Q1 - 2007 Q3. The results of the model using both linear and non-linear specifications indicate that there is no direct impact of oil price shock on the economic activity. The shock of oil prices affects economic activity indirectly. The most significant channel by which the effects of the shock are transmitted is the government's spending. (author)

  17. The Feldstein-Horioka Hypothesis in Countries with Varied Levels of Economic Development

    Directory of Open Access Journals (Sweden)

    Piotr Misztal

    2011-06-01

    Full Text Available This article aims to analyse the Feldstein-Horioka hypothesis, which suggests a strong correlation between investments and savings in advanced economies. Additionally, the analysis of the Feldstein- Horioka hypothesis was expanded to include emerging markets and developing economies in order to provide a thorough analysis of this issue.1 The paper utilises a research method based on bibliographic studies in macroeconomics and international finances as well as econometric methods (the vector autoregressive model - VAR. All statistical data used in the paper are taken from the statistical database of the International Monetary Fund (World Economic Outlook Database.

  18. Kepler AutoRegressive Planet Search (KARPS)

    Science.gov (United States)

    Caceres, Gabriel

    2018-01-01

    One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The Kepler AutoRegressive Planet Search (KARPS) project implements statistical methodology associated with autoregressive processes (in particular, ARIMA and ARFIMA) to model stellar lightcurves in order to improve exoplanet transit detection. We also develop a novel Transit Comb Filter (TCF) applied to the AR residuals which provides a periodogram analogous to the standard Box-fitting Least Squares (BLS) periodogram. We train a random forest classifier on known Kepler Objects of Interest (KOIs) using select features from different stages of this analysis, and then use ROC curves to define and calibrate the criteria to recover the KOI planet candidates with high fidelity. These statistical methods are detailed in a contributed poster (Feigelson et al., this meeting).These procedures are applied to the full DR25 dataset of NASA’s Kepler mission. Using the classification criteria, a vast majority of known KOIs are recovered and dozens of new KARPS Candidate Planets (KCPs) discovered, including ultra-short period exoplanets. The KCPs will be briefly presented and discussed.

  19. Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

    Science.gov (United States)

    Fu, Xiao; Huang, Kejun; Hong, Mingyi; Sidiropoulos, Nicholas D.; So, Anthony Man-Cho

    2017-08-01

    Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis (PCA) that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation which has recently gained renewed interest in multilingual processing and speech modeling. The classic MAX-VAR GCCA problem can be solved optimally via eigen-decomposition of a matrix that compounds the (whitened) correlation matrices of the views; but this solution has serious scalability issues, and is not directly amenable to incorporating pertinent structural constraints such as non-negativity and sparsity on the canonical components. We posit regularized MAX-VAR GCCA as a non-convex optimization problem and propose an alternating optimization (AO)-based algorithm to handle it. Our algorithm alternates between {\\em inexact} solutions of a regularized least squares subproblem and a manifold-constrained non-convex subproblem, thereby achieving substantial memory and computational savings. An important benefit of our design is that it can easily handle structure-promoting regularization. We show that the algorithm globally converges to a critical point at a sublinear rate, and approaches a global optimal solution at a linear rate when no regularization is considered. Judiciously designed simulations and large-scale word embedding tasks are employed to showcase the effectiveness of the proposed algorithm.

  20. To center or not to center? Investigating inertia with a multilevel autoregressive model

    Directory of Open Access Journals (Sweden)

    Ellen L. Hamaker

    2015-01-01

    Full Text Available Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion, cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship. This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction, cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

  1. Forecasting with periodic autoregressive time series models

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    1999-01-01

    textabstractThis paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption

  2. MONETARY POLICY TRANSMISSION MECHANISM AND TVP-VAR MODEL

    Directory of Open Access Journals (Sweden)

    Andreea ROŞOIU

    2013-12-01

    Full Text Available The transmission of monetary policy to the economy is a subject of major importance for central banks because, by using these measures, central banks can achieve their purpose of ensuring price stability without neglecting the objective of sustainable economic growth. In order to analyze the evolution of the monetary policy transmission mechanism in Romania, a time varying structural vector autoregression model is estimated, by using a Markov Chain Monte Carlo algorithm for the posterior evolution. The conclusions of the empirical study are: both systematic and non-systematic monetary policy have changed during the investigated period of time, the systematic response of the interest rate to shocks in inflation and unemployment being faster over the recent period. Also, non-policy shocks seem more important than interest rate shocks in explaining inflation and unemployment evolution.

  3. Survey of cyclopids (Crustacea, Copepoda in Brazil and preliminary screening of their potential as dengue vector predators

    Directory of Open Access Journals (Sweden)

    Santos Luciana Urbano dos

    1997-01-01

    Full Text Available INTRODUCTION: Cyclopid copepods are known to be good mosquito controllers, specially as regards the larvae of the dengue vectors Aedes aegypti and Ae. albopictus. MATERIAL AND METHOD: The objective of the study was to survey the local copepod fauna and search for new strains of M. longisetus var. longisetus, comparing the potential of the samples found with the current strain ML-01 against Ae. albopictus larvae, under laboratory conditions. Eleven bodies of water in Campinas, SP, Brazil, were screened for copepods by collecting 1.5 l of water from each of then. The predatory potential of adults copepods was evaluated over 24 h, in the laboratory, for groups of 5 individuals preying upon 30 first instar Ae. albopictus larvae. RESULTS AND CONCLUSION: The following cyclopid species were found: Metacyclops mendocinus, Tropocyclops prasinus, Eucyclops sp, Eucyclops serrulatus, Eucyclops solitarius, Eucyclops ensifer, Macrocyclops albidus var. albidus and Mesocyclops longisetus var. longisetus. The predatory potential of these copepods ranged from nil to 97.3%. A sample collected in the field containing only M. longisetus var. longisetus showed the best control efficiency with no significant difference from a three-year old laboratory culture (ML-01 of the same species evaluated for comparison. The sample with few M. albidus var. albidus was ranked in second place showing an average 25.9% efficiency. The use of copepods in trap tires as dengue vector controllers is discussed.

  4. Kepler AutoRegressive Planet Search

    Science.gov (United States)

    Caceres, Gabriel Antonio; Feigelson, Eric

    2016-01-01

    The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real

  5. Molecular and physiological diversity among Verticillium fungicola var. fungicola and var. aleophilum

    NARCIS (Netherlands)

    Largeteau, M.L.; Baars, J.J.P.; Savoie, J.M.

    2006-01-01

    The genetic and physiological variability of Verticillium fungicola var. aleophilum responsible for Agaricus bisporus dry bubble disease in North America is well documented but little is known about the var. fungicola affecting European crops. Variability was assessed within this variety and

  6. Linear and non-linear autoregressive models for short-term wind speed forecasting

    International Nuclear Information System (INIS)

    Lydia, M.; Suresh Kumar, S.; Immanuel Selvakumar, A.; Edwin Prem Kumar, G.

    2016-01-01

    Highlights: • Models for wind speed prediction at 10-min intervals up to 1 h built on time-series wind speed data. • Four different multivariate models for wind speed built based on exogenous variables. • Non-linear models built using three data mining algorithms outperform the linear models. • Autoregressive models based on wind direction perform better than other models. - Abstract: Wind speed forecasting aids in estimating the energy produced from wind farms. The soaring energy demands of the world and minimal availability of conventional energy sources have significantly increased the role of non-conventional sources of energy like solar, wind, etc. Development of models for wind speed forecasting with higher reliability and greater accuracy is the need of the hour. In this paper, models for predicting wind speed at 10-min intervals up to 1 h have been built based on linear and non-linear autoregressive moving average models with and without external variables. The autoregressive moving average models based on wind direction and annual trends have been built using data obtained from Sotavento Galicia Plc. and autoregressive moving average models based on wind direction, wind shear and temperature have been built on data obtained from Centre for Wind Energy Technology, Chennai, India. While the parameters of the linear models are obtained using the Gauss–Newton algorithm, the non-linear autoregressive models are developed using three different data mining algorithms. The accuracy of the models has been measured using three performance metrics namely, the Mean Absolute Error, Root Mean Squared Error and Mean Absolute Percentage Error.

  7. Autoregressive Moving Average Graph Filtering

    OpenAIRE

    Isufi, Elvin; Loukas, Andreas; Simonetto, Andrea; Leus, Geert

    2016-01-01

    One of the cornerstones of the field of signal processing on graphs are graph filters, direct analogues of classical filters, but intended for signals defined on graphs. This work brings forth new insights on the distributed graph filtering problem. We design a family of autoregressive moving average (ARMA) recursions, which (i) are able to approximate any desired graph frequency response, and (ii) give exact solutions for tasks such as graph signal denoising and interpolation. The design phi...

  8. Interval Forecast for Smooth Transition Autoregressive Model ...

    African Journals Online (AJOL)

    In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...

  9. Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

    Science.gov (United States)

    Levine, Matthew E; Albers, David J; Hripcsak, George

    2016-01-01

    Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

  10. New interval forecast for stationary autoregressive models ...

    African Journals Online (AJOL)

    In this paper, we proposed a new forecasting interval for stationary Autoregressive, AR(p) models using the Akaike information criterion (AIC) function. Ordinarily, the AIC function is used to determine the order of an AR(p) process. In this study however, AIC forecast interval compared favorably with the theoretical forecast ...

  11. Multistage Stochastic Programming via Autoregressive Sequences

    Czech Academy of Sciences Publication Activity Database

    Kaňková, Vlasta

    2007-01-01

    Roč. 15, č. 4 (2007), s. 99-110 ISSN 0572-3043 R&D Projects: GA ČR GA402/07/1113; GA ČR(CZ) GA402/06/0990; GA ČR GD402/03/H057 Institutional research plan: CEZ:AV0Z10750506 Keywords : Economic proceses * Multistage stochastic programming * autoregressive sequences * individual probability constraints Subject RIV: BB - Applied Statistics, Operational Research

  12. The relationship between oil price shocks and China's macro-economy. An empirical analysis

    International Nuclear Information System (INIS)

    Du, Limin; Yanan, He; Wei; Chu

    2010-01-01

    This paper investigates the relationship between the world oil price and China's macro-economy based on a monthly time series from 1995:1 to 2008:12, using the method of multivariate vector autoregression (VAR). The results show that the world oil price affects the economic growth and inflation of China significantly, and the impact is non-linear. On the other hand, China's economic activity fails to affect the world oil price, which means that the world oil price is still exogenous with respect to China's macro-economy in time series sense, and China has not yet had an oil pricing power in the world oil markets. The structural stability tests demonstrate that there is a structural break in the VAR model because of the reforms of China's oil pricing mechanism, thus it is more appropriate to break the whole sample into different sub-samples for the estimation of the model. (author)

  13. Energy and economic growth in the USA: a multivariate approach

    International Nuclear Information System (INIS)

    Stern, D.I.

    1993-01-01

    This paper examines the casual relationship between Gross Domestic Product and energy use for the period 1947-90 in the United States of America. The relationship between energy use and economic growth has been examined by both biophysical and neoclassical economists. In particular, several studies have tested for the presence of a causal relationships (in the Granger sense) between energy use and economic growth. However, these tests do not allow a direct test of the relative explanatory powers of the neoclassical and biophysical models. A multivariate adaptation of the test-vector autoregression (VAR) does allow such a test. A VAR of GDP, energy use, capital stock and employment is estimated and Granger tests for causal relationships between the variables are carried out. Although there is no evidence that gross energy use Granger causes GDP, a measure of final energy use adjusted for changing fuel composition does Granger cause GDP. (author)

  14. Prediction of Machine Tool Condition Using Support Vector Machine

    International Nuclear Information System (INIS)

    Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

    2011-01-01

    Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

  15. Factors Impacting Bank Net Interest Margin and the Role of Monetary Policy: Evidence from Turkey

    Directory of Open Access Journals (Sweden)

    Muhammed Hasan Yılmaz

    2017-10-01

    Full Text Available In this study, we investigate factors affecting net interest margin (NIM of commercial banks in Turkey. Especially, our results highlight the relation between unconventional monetary policy shocks and bank margins. To this end, first, we conduct an identification analysis about which parameters of asymmetric interest corridor framework are important in explaining variations in NIM. Using industry-level data, we show that there exists a pass through from BIST interbank overnight repo/reverse repo market rate and weighted average cost of funding (WACF to bank loan and deposit rates. As a result of reduced-form Vector Autoregression (VAR analysis we find the existence of a transmission mechanism from BIST rate and WACF to commercial loan rate, consumer loan rate and deposit rate. Same pass through to loan and deposit rates is also shown in individual bank level with the Panel Vector Autoregression (Panel VAR analysis in the case of 16 commercial banks in Turkey during the period 2011Q1-2016Q1. After the identification analysis, we examine the relationship between NIM and policy rates through System Generalized Method of Moments (GMM techniques by controlling bank specific, industry related and macroeconomic factors. We find that a change in the monetary policy rate has significant and positive impact on NIM. Among bank-specific factors, equity ratio and operating expenses are found to be significantly affecting NIM during the sample period. Our empirical findings also stress the significance of lag values of NIM. Estimations conducted with standardized variables indicate that economic significance of lag values and bank specific variables are larger than that of policy.

  16. Taxonomical studies on endemic scorzonera pygmaea var. pygmaea and var. nutans stat. nov. (asteraceae) from turkey

    International Nuclear Information System (INIS)

    Koyuncu, O.; Kus, G.

    2014-01-01

    The taxonomic status of Scorzonera pygmaea var. pygmaea and var. nutans belonging to the tribe. cichoreae (Asteraceae). S. pygmaea samples were collected from Arayit mountain. We suggest that these two subspecies should be classified as varietes because of their morphological and anatomical characteristics, ecological and geographical similarities. Moreover being together in the same localities of these under species taxa supports our opinion, i.e. S. pygmaea Sibth. and Sm. var. pygmaea stat. nov. and S. pygmaea Sibth. and Sm. var. nutans (Czeczott) O. Koyuncu and Yaylac, stat. nov. (author)

  17. Combined effect of seaweed (Sargassum wightii) and Bacillus thuringiensis var. israelensis on the coastal mosquito,Anopheles sundaicus, in Tamil Nadu, India

    Science.gov (United States)

    Studies were made of the extract of Sargassum wightii combined with Bacillus thuringiensis var. israelensis (Bti) for control of the malaria vector Anopheles sundaicus. Treatment of mosquito larvae with 0.001% S. wightii extract indicated median lethal concentrations (LC50) of 88, 73, 134, 156, and...

  18. Application of autoregressive moving average model in reactor noise analysis

    International Nuclear Information System (INIS)

    Tran Dinh Tri

    1993-01-01

    The application of an autoregressive (AR) model to estimating noise measurements has achieved many successes in reactor noise analysis in the last ten years. The physical processes that take place in the nuclear reactor, however, are described by an autoregressive moving average (ARMA) model rather than by an AR model. Consequently more correct results could be obtained by applying the ARMA model instead of the AR model to reactor noise analysis. In this paper the system of the generalised Yule-Walker equations is derived from the equation of an ARMA model, then a method for its solution is given. Numerical results show the applications of the method proposed. (author)

  19. Likelihood inference for a nonstationary fractional autoregressive model

    DEFF Research Database (Denmark)

    Johansen, Søren; Ørregård Nielsen, Morten

    2010-01-01

    This paper discusses model-based inference in an autoregressive model for fractional processes which allows the process to be fractional of order d or d-b. Fractional differencing involves infinitely many past values and because we are interested in nonstationary processes we model the data X1......,...,X_{T} given the initial values X_{-n}, n=0,1,..., as is usually done. The initial values are not modeled but assumed to be bounded. This represents a considerable generalization relative to all previous work where it is assumed that initial values are zero. For the statistical analysis we assume...... the conditional Gaussian likelihood and for the probability analysis we also condition on initial values but assume that the errors in the autoregressive model are i.i.d. with suitable moment conditions. We analyze the conditional likelihood and its derivatives as stochastic processes in the parameters, including...

  20. Analysis list: Su(var)205 [Chip-atlas[Archive

    Lifescience Database Archive (English)

    Full Text Available Su(var)205 Adult,Embryo,Larvae + dm3 http://dbarchive.biosciencedbc.jp/kyushu-u/dm3.../target/Su(var)205.1.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/dm3/target/Su(var)205.5.tsv http://dbarc...hive.biosciencedbc.jp/kyushu-u/dm3/target/Su(var)205.10.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/dm3/c...olo/Su(var)205.Adult.tsv,http://dbarchive.biosciencedbc.jp/kyushu-u/dm3/colo/Su(var)205.Embryo.tsv,http:...//dbarchive.biosciencedbc.jp/kyushu-u/dm3/colo/Su(var)205.Larvae.tsv http://dbarchive

  1. 4D-Var Developement at GMAO

    Science.gov (United States)

    Pelc, Joanna S.; Todling, Ricardo; Akkraoui, Amal El

    2014-01-01

    The Global Modeling and Assimilation Offce (GMAO) is currently using an IAU-based 3D-Var data assimilation system. GMAO has been experimenting with a 3D-Var-hybrid version of its data assimilation system (DAS) for over a year now, which will soon become operational and it will rapidly progress toward a 4D-EnVar. Concurrently, the machinery to exercise traditional 4DVar is in place and it is desirable to have a comparison of the traditional 4D approach with the other available options, and evaluate their performance in the Goddard Earth Observing System (GEOS) DAS. This work will also explore the possibility for constructing a reduced order model (ROM) to make traditional 4D-Var computationally attractive for increasing model resolutions. Part of the research on ROM will be to search for a suitably acceptable space to carry on the corresponding reduction. This poster illustrates how the IAU-based 4D-Var assimilation compares with our currently used IAU-based 3D-Var.

  2. Data Assimilation of Lightning using 1D+3D/4D WRF Var Assimilation Schemes with Non-Linear Observation Operators

    Science.gov (United States)

    Navon, M. I.; Stefanescu, R.; Fuelberg, H. E.; Marchand, M.

    2012-12-01

    NASA's launch of the GOES-R Lightning Mapper (GLM) in 2015 will provide continuous, full disc, high resolution total lightning (IC + CG) data. The data will be available at a horizontal resolution of approximately 9 km. Compared to other types of data, the assimilation of lightning data into operational numerical models has received relatively little attention. Previous efforts of lightning assimilation mostly have employed nudging. This paper will describe the implementation of 1D+3D/4D Var assimilation schemes of existing ground-based WTLN (Worldwide Total Lightning Network) lightning observations using non-linear observation operators in the incremental WRFDA system. To mimic the expected output of GLM, the WTLN data were used to generate lightning super-observations characterized by flash rates/81 km2/20 min. A major difficulty associated with variational approaches is the complexity of the observation operator that defines the model equivalent of lightning. We use Convective Available Potential Energy (CAPE) as a proxy between lightning data and model variables. This operator is highly nonlinear. Marecal and Mahfouf (2003) have shown that nonlinearities can prevent direct assimilation of rainfall rates in the ECMWF 4D-VAR (using the incremental formulation proposed by Courtier et al. (1994)) from being successful. Using data from the 2011 Tuscaloosa, AL tornado outbreak, we have proved that the direct assimilation of lightning data into the WRF 3D/4D - Var systems is limited due to this incremental approach. Severe threshold limits must be imposed on the innovation vectors to obtain an improved analysis. We have implemented 1D+3D/4D Var schemes to assimilate lightning observations into the WRF model. Their use avoids innovation vector constrains from preventing the inclusion of a greater number of lightning observations Their use also minimizes the problem that nonlinearities in the moist convective scheme can introduce discontinuities in the cost function

  3. The Dynamic Effects of Entrepreneurship on Regional Economic Growth

    DEFF Research Database (Denmark)

    Matejovsky, Lukas; Mohapatra, Sandeep; Steiner, Bodo

    2014-01-01

    This study explores the temporal pattern of income disparity for Canadian provinces in two estimation steps. First, an econometric growth regression model is applied to identify the impact of entrepreneurship on regional economic growth. The estimation results suggest that entrepreneurship......, measured in terms of the selfemployment rate, plays a pivotal role in determining regional development in Canada. Second, a dynamic vector autoregression (VAR) model is employed to predict the long-run regional growth effects that result from policy shocks affecting entrepreneurship. Compared to other...... growth drivers, entrepreneurship is found to have more pronounced and long-term stimulative effects on regional development for the period of 1987 to 2007...

  4. The Nexus between Higher Education and Economic Growth: An Empirical Investigation for Pakistan

    Directory of Open Access Journals (Sweden)

    Amatul R. Chaudhary

    2009-06-01

    Full Text Available The study investigates the role of higher education in economic growth for Pakistan between 1972 and 2005 using the application of Johansen Cointegration and Toda & Yamamoto (1995 Causality approach in Vector Autoregressive (VAR framework. It examines whether higher education affect long run economic growth in Pakistan. The empirical analysis reveals that there is a long run relationship between economic growth and higher education, which suggests that these variables are necessary for each other. The empirical results of causality test indicate that there exists a unidirectional causality running from economic growth to higher education and no other direction of causality found between these variables.

  5. CAUSAL RELATIONSHIPS BETWEEN GRAIN, MEAT PRICES AND EXCHANGE RATES

    Directory of Open Access Journals (Sweden)

    Naveen Musunuru

    2017-10-01

    Full Text Available Understanding agricultural commodity price relationships are important as they help producers improve their awareness regarding production costs and ultimately aid in income determination. The present paper empirically examines the dynamic interrelationships among grain, meat prices and the U.S. dollar exchange rate. Johansen cointegration tests reveal no cointegrating relationships among the study variables. Majority of the commodities studied in the paper exhibited unidirectional causality except for corn and lean hogs. The vector autoregression (VAR model results indicate that the grain and meat prices are influenced by their own past prices. The role of exchange rates is found to be limited in linking the agricultural commodities.

  6. Forecasting nuclear power supply with Bayesian autoregression

    International Nuclear Information System (INIS)

    Beck, R.; Solow, J.L.

    1994-01-01

    We explore the possibility of forecasting the quarterly US generation of electricity from nuclear power using a Bayesian autoregression model. In terms of forecasting accuracy, this approach compares favorably with both the Department of Energy's current forecasting methodology and their more recent efforts using ARIMA models, and it is extremely easy and inexpensive to implement. (author)

  7. Robust bayesian analysis of an autoregressive model with ...

    African Journals Online (AJOL)

    In this work, robust Bayesian analysis of the Bayesian estimation of an autoregressive model with exponential innovations is performed. Using a Bayesian robustness methodology, we show that, using a suitable generalized quadratic loss, we obtain optimal Bayesian estimators of the parameters corresponding to the ...

  8. A vector autoregressive model for electricity prices subject to long memory and regime switching

    International Nuclear Information System (INIS)

    Haldrup, Niels; Nielsen, Frank S.; Nielsen, Morten Oerregaard

    2010-01-01

    A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the observed regime states as well as the possibility of fractional cointegration. The model is motivated by the dynamics of electricity prices where the transmission of power is subject to occasional congestion periods. For a system of bilateral prices non-congestion means that electricity prices are identical whereas congestion makes prices depart. Hence, the joint price dynamics implies switching between a univariate price process under non-congestion and a bivariate price process under congestion. At the same time, it is an empirical regularity that electricity prices tend to show a high degree of long memory, and thus that prices may be fractionally cointegrated. Analysis of Nord Pool data shows that even though the prices are identical under non-congestion, the prices are not, in general, fractionally cointegrated in the congestion state. Hence, in most cases price convergence is a property following from regime switching rather than a conventional error correction mechanism. Finally, the suggested model is shown to deliver forecasts that are more precise compared to competing models. (author)

  9. New prediction for the direct CP-violating parameter var-epsilon prime/var-epsilon and the ΔI=1/2 rule

    International Nuclear Information System (INIS)

    Wu, Yue-Liang

    2001-01-01

    The low-energy dynamics of QCD is investigated with special attention paid to the matching between QCD and chiral perturbation theory (ChPT), and also to some useful algebraic chiral operator relations which survive even when we include chiral loop corrections. It then allows us to evaluate the hadronic matrix elements below the energy scale Λ χ ≅1GeV. Based on the new analyses, we present a consistent prediction for both the direct CP-violating parameter var-epsilonprime/var-epsilon and the ΔI=1/2 rule in kaon decays. In the leading 1/N c approximation, the isospin amplitudes A 0 and A 2 are found to agree well with the data, and the direct CP-violating parameter var-epsilonprime/var-epsilon is predicted to be large, which also confirms our earlier conclusion. Its numerical value is var-epsilonprime/var-epsilon=23.6 -7.8 +12.4 x10 -4 (Imλ t /= 1.2x10 -4 ) which is no longer sensitive to the strange quark mass due to the matching conditions. Taking into account a simultaneous consistent analysis on the isospin amplitudes A 0 and A 2 , the ratio var-epsilonprime/var-epsilon is in favor of the values var-epsilonprime/var-epsilon=(20±9)x10 -4

  10. Evaluating Liquid and Granular Bacillus thuringiensis var. israelensis Broadcast Applications for Controlling Vectors of Dengue and Chikungunya Viruses in Artificial Containers and Tree Holes.

    Science.gov (United States)

    Harwood, James F; Farooq, Muhammad; Turnwall, Brent T; Richardson, Alec G

    2015-07-01

    The principal vectors of chikungunya and dengue viruses typically oviposit in water-filled artificial and natural containers, including tree holes. Despite the risk these and similar tree hole-inhabiting mosquitoes present to global public health, surprisingly few studies have been conducted to determine an efficient method of applying larvicides specifically to tree holes. The Stihl SR 450, a backpack sprayer commonly utilized during military and civilian vector control operations, may be suitable for controlling larval tree-hole mosquitoes, as it is capable of delivering broadcast applications of granular and liquid dispersible formulations of Bacillus thuringiensis var. israelensis (Bti) to a large area relatively quickly. We compared the application effectiveness of two granular (AllPro Sustain MGB and VectoBac GR) and two liquid (Aquabac XT and VectoBac WDG) formulations of Bti in containers placed on bare ground, placed beneath vegetative cover, and hung 1.5 or 3 m above the ground to simulate tree holes. Aedes aegypti (L.) larval mortality and Bti droplet and granule density data (when appropriate) were recorded for each formulation. Overall, granular formulations of Bti resulted in higher mortality rates in the simulated tree-hole habitats, whereas applications of granular and liquid formulations resulted in similar levels of larval mortality in containers placed on the ground in the open and beneath vegetation. Published by Oxford University Press on behalf of Entomological Society of America 2015. This work is written by US Government employees and is in the public domain in the US.

  11. The Gaussian Graphical Model in Cross-Sectional and Time-Series Data.

    Science.gov (United States)

    Epskamp, Sacha; Waldorp, Lourens J; Mõttus, René; Borsboom, Denny

    2018-04-16

    We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential causal relationships between observed variables. We describe the utility in three kinds of psychological data sets: data sets in which consecutive cases are assumed independent (e.g., cross-sectional data), temporally ordered data sets (e.g., n = 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In time-series analysis, the GGM can be used to model the residual structure of a vector-autoregression analysis (VAR), also termed graphical VAR. Two network models can then be obtained: a temporal network and a contemporaneous network. When analyzing data from multiple subjects, a GGM can also be formed on the covariance structure of stationary means-the between-subjects network. We discuss the interpretation of these models and propose estimation methods to obtain these networks, which we implement in the R packages graphicalVAR and mlVAR. The methods are showcased in two empirical examples, and simulation studies on these methods are included in the supplementary materials.

  12. Survival and infectivity of Sarcoptes scabiei var. canis and var. hominis.

    Science.gov (United States)

    Arlian, L G; Runyan, R A; Achar, S; Estes, S A

    1984-08-01

    Sarcoptes scabiei var. canis served as a suitable model for the study of S. scabiei var. hominis survival. S. scabiei var. canis and var. hominis mites were found to survive off the host for 24 to 36 hours at room conditions (21 degrees C and 40% to 80% relative humidity [RH]), and the canine variety survived 19 days at 10 degrees C and 97% RH. Female mites survived decidedly longer than male mites at comparable conditions. Generally, higher RH values and lower temperatures favored survival, whereas higher temperature and lower RH led to early death. Most canine scabies mites that were held off the host for 36 hours at 75% RH and 22 degrees to 24 degrees C remained infective and penetrated when returned to the host. Live mites of the human variety that were recovered from bed linen slept on by infested patients would also penetrate a host after being held off a host for 96 hours in alternating 12-hour periods of room conditions and refrigeration. Penetration required less than 30 minutes for all life stages of both varieties, and it was accomplished by a mite secretion that dissolved the host tissue. Dislodged mites, particularly those in close proximity to the source, can be a likely source of infestation.

  13. A structural VAR analysis of electricity consumption and real GDP: Evidence from the G7 countries

    International Nuclear Information System (INIS)

    Narayan, Paresh Kumar; Narayan, Seema; Prasad, Arti

    2008-01-01

    In this paper, we depart from the literature on electricity consumption-real GDP in that for the first time we examine the reaction of real GDP to shocks in electricity consumption. To achieve this goal, we use the structural vector autoregressive (SVAR) model and examine the impact of electricity consumption shocks on real GDP for the G7 countries. We find that except for the USA, electricity consumption has a statistically significant positive impact on real GDP over short horizons. This finding implies that except for the USA, electricity conservation policies will hurt real GDP in the G7 countries

  14. Dimension reduction of frequency-based direct Granger causality measures on short time series.

    Science.gov (United States)

    Siggiridou, Elsa; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris

    2017-09-01

    The mainstream in the estimation of effective brain connectivity relies on Granger causality measures in the frequency domain. If the measure is meant to capture direct causal effects accounting for the presence of other observed variables, as in multi-channel electroencephalograms (EEG), typically the fit of a vector autoregressive (VAR) model on the multivariate time series is required. For short time series of many variables, the estimation of VAR may not be stable requiring dimension reduction resulting in restricted or sparse VAR models. The restricted VAR obtained by the modified backward-in-time selection method (mBTS) is adapted to the generalized partial directed coherence (GPDC), termed restricted GPDC (RGPDC). Dimension reduction on other frequency based measures, such the direct directed transfer function (dDTF), is straightforward. First, a simulation study using linear stochastic multivariate systems is conducted and RGPDC is favorably compared to GPDC on short time series in terms of sensitivity and specificity. Then the two measures are tested for their ability to detect changes in brain connectivity during an epileptiform discharge (ED) from multi-channel scalp EEG. It is shown that RGPDC identifies better than GPDC the connectivity structure of the simulated systems, as well as changes in the brain connectivity, and is less dependent on the free parameter of VAR order. The proposed dimension reduction in frequency measures based on VAR constitutes an appropriate strategy to estimate reliably brain networks within short-time windows. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. The effects of the fungus Metarhizium anisopliae var. acridum on different stages of Lutzomyia longipalpis (Diptera: Psychodidae).

    Science.gov (United States)

    Amóra, Sthenia Santos Albano; Bevilaqua, Claudia Maria Leal; Feijó, Francisco Marlon Carneiro; Pereira, Romeika Hermínia de Macedo Assunção; Alves, Nilza Dutra; Freire, Fúlvio Aurélio de Morais; Kamimura, Michel Toth; de Oliveira, Diana Magalhães; Luna-Alves Lima, Elza Aurea; Rocha, Marcos Fábio Gadelha

    2010-03-01

    The control of Visceral Leishmaniasis (VL) vector is often based on the application of chemical residual insecticide. However, this strategy has not been effective. The continuing search for an appropriate vector control may include the use of biological control. This study evaluates the effects of the fungus Metarhizium anisopliae var. acridum on Lutzomyia longipalpis. Five concentrations of the fungus were utilized, 1 x 10(4) to 1 x 10(8) conidia/ml, accompanied by controls. The unhatched eggs, larvae and dead adults previously exposed to fungi were sown to reisolate the fungi and analysis of parameters of growth. The fungus was subsequently identified by PCR and DNA sequencing. M. anisopliae var. acridum reduced egg hatching by 40%. The mortality of infected larvae was significant. The longevity of infected adults was lower than that of negative controls. The effects of fungal infection on the hatching of eggs laid by infected females were also significant. With respect to fungal growth parameters post-infection, only vegetative growth was not significantly higher than that of the fungi before infection. The revalidation of the identification of the reisolated fungus was confirmed post-passage only from adult insects. In terms of larvae mortality and the fecundity of infected females, the results were significant, proving that the main vector species of VL is susceptible to infection by this entomopathogenic fungus in the adult stage. Copyright 2009 Elsevier B.V. All rights reserved.

  16. Analisis Penerapan Kebijakan Moneter Suku Bunga Jangka Pendek pada Variabel-variabel Endogen MakroEkonomi Indonesia

    Directory of Open Access Journals (Sweden)

    Sari Damayanti

    2014-11-01

    Full Text Available This study analyzed the impact of the implementation of monetary policy through short-term interest rates setting on the variation that occurs in the endogenous variables of Indonesian macro economy in the period of 2000-2009 by implementing the Structural Vector Autoregressive approach (SVAR which is the development of Vector Autoregressive (VAR modelling with Eviews program. By careful examination of the results, this study indicates that the value of interest rate changes is significantly associated with shocks that are associated with monetary policy. The monetary sector is heavily influenced by real GDP shock, liquidity, and inflation shock. However, the monetary sector is only slightly affected by the decomposition of the variance of the exchange rate, which is very sensitive to the inflation shock. The study also indicates that the endogenous variables in the value of changes in interest rates and real exchange rate of rupiah will be close to convergence in the long term. The endogenous variables are more susceptible to changes in variables derived from domestic, such as the level of demand for domestic currency liquidity, compared to variables derived from international capital exposure. Thus, the value of the variable interest rate changes can be used to reduce the potential risks derived from domestic money demand shock.

  17. Global oil glut and sanctions: The impact on Putin’s Russia

    International Nuclear Information System (INIS)

    Tuzova, Yelena; Qayum, Faryal

    2016-01-01

    The Russian economy is highly responsive to oil price fluctuations. At the start of 2014, the country was already suffering from the weak economic growth, partly due to the ongoing crisis in Ukraine and Western sanctions. The recent plunge in global oil prices put even further strain on the Russian economy. This paper analyzes the dynamic relationship between oil price shocks, economic sanctions, and leading macroeconomic indicators in Russia. We apply a vector autoregression (VAR) to quantify the effects of oil price shocks as well as western economic sanctions on real GDP, real effective exchange rate, inflation, real fiscal expenditures, real consumption expenditures, and external trade using quarterly data from 1999:1 until 2015:1. Our results show a significant impact of oil prices on the Russian economy. We predict that Russia’s economic outlook is not very optimistic. If sanctions remain until the end of 2017, the quarter-to-quarter real GDP will contract on average by 19 percent over the next two years. - Highlights: • The impact of the recent decline in oil prices and western sanctions is analyzed. • A vector autoregression model is used to do the forecast for Russia. • The real GDP is likely to contract by 19 percent over the next two years.

  18. Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intraday Range

    NARCIS (Netherlands)

    C.W.S. Chen (Cathy); R. Gerlach (Richard); B.B.K. Hwang (Bruce); M.J. McAleer (Michael)

    2011-01-01

    textabstractValue-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We propose some novel nonlinear threshold conditional autoregressive VaR (CAViar) models that incorporate intra-day

  19. ANALISIS EFEKTIVITAS KEBIJAKAN MONETER DAN KEBIJAKAN FISKAL DALAM MENGATASI INFLASI DI INDONESIA

    Directory of Open Access Journals (Sweden)

    Reni Opriyanti

    2017-10-01

    Full Text Available Unstable inflation is influenced by economic conditions. Macroeconomic conditions in Indonesia make inflation increase or decrease. The policies taken by the government and the central bank determine the size of inflation. Community consumption patterns also play a role in increasing inflation. The purpose of this study is to determine the most effective policy in overcoming inflation, using the Vector Autoregressive (VAR model to estimate the research variables. Impulse response function and variance decomposition that describes how and how the influence of inflation fluctuations. VAR estimates show significant inflation influenced by the money supply and SBI interest rate in the first lag. Meanwhile, taxes and government spending are significant in the second lag. Impulse response analysis shows that inflation response is fastest and strongest by the money supply. While the description of variance decomposition, the variations described inflation most affect the change of inflation itself and second order is the money supply.

  20. Business cycles in oil economies

    International Nuclear Information System (INIS)

    Al-Mutairi, N.H.

    1991-01-01

    This study examines the impact of oil price shocks on output fluctuations of several oil-exporting economies. In most studies of business cycles, the role of oil price is ignored; the few studies that use oil price as one of the variables in the system focus on modeling oil-importing economies. The vector autoregression (VAR) technique is used to consider the cases of Norway, Nigeria, and Mexico. Both atheoretical and 'structural' VARs are estimated to determine the importance of oil price impulses on output variations. The study reports two types of results: variance decomposition and impulse response functions, with particular emphasis on the issues of stationarity and co-integration among the series. The empirical results suggest that shocks to oil price are important in explaining output variations. In most cases, shocks to oil price are shown to explain more than 20% of the forecast variance of output over a 40-quarter horizon

  1. The Impact of Oil Price Volatility on Macroeconomic Activity in Russia

    Directory of Open Access Journals (Sweden)

    Katsuya Ito

    2010-07-01

    Full Text Available Since the beginning of the 1980s a large number of studies using a vector autoregressive (VAR model have been made on the macroeconomic effects of oil price changes. However, surprisingly few studies have so far focused on Russia, the world’s second largest oil exporter. The purpose of this paper is to empirically examine the impact of oil prices on the macroeconomic variables in Russia using the VAR model. The time span covered by the series is from 1994:Q1 to 2009:Q3, giving 63 observations. The analysis leads to the finding that a 1% increase (decrease in oil prices contributes to the depreciation (appreciation of the exchange rate by 0.17% in the long run, whereas it leads to a 0.46% GDP growth (decline. Likewise, we find that in the short run (8 quarters rising oil prices cause not only the GDP growth and the exchange rate depreciation, but also a marginal increase in inflation rate.

  2. On robust forecasting of autoregressive time series under censoring

    OpenAIRE

    Kharin, Y.; Badziahin, I.

    2009-01-01

    Problems of robust statistical forecasting are considered for autoregressive time series observed under distortions generated by interval censoring. Three types of robust forecasting statistics are developed; meansquare risk is evaluated for the developed forecasting statistics. Numerical results are given.

  3. Identification and characterization of the Spodoptera Su(var) 3-9 histone H3K9 trimethyltransferase and its effect in AcMNPV infection.

    Science.gov (United States)

    Li, Binbin; Li, Sisi; Yin, Juan; Zhong, Jiang

    2013-01-01

    Histone H3-lysine(9) (H3K9) trimethyltransferase gene Su(var) 3-9 was cloned and identified in three Spodoptera insects, Spodopterafrugiperda (S. frugiperda), S. exigua and S. litura. Sequence analysis showed that Spodoptera Su(var) 3-9 is highly conserved evolutionarily. Su(var) 3-9 protein was found to be localized in the nucleus in Sf9 cells, and interact with histone H3, and the heterochromatin protein 1a (HP1a) and HP1b. A dose-dependent enzymatic activity was found at both 27 °C and 37 °C in vitro, with higher activity at 27 °C. Addition of specific inhibitor chaetocin resulted in decreased histone methylation level and host chromatin relaxation. In contrast, overexpression of Su(var) 3-9 caused increased histone methylation level and cellular genome compaction. In AcMNV-infected Sf9 cells, the transcription of Su(var) 3-9 increased at late time of infection, although the mRNA levels of most cellular genes decreased. Pre-treatment of Sf9 cells with chaetocin speeded up viral DNA replication, and increased the transcription level of a variety of virus genes, whereas in Sf9 cells pre-transformed with Su(var) 3-9 expression vector, viral DNA replication slow down slightly. These findings suggest that Su(var) 3-9 might participate in the viral genes expression an genome replication repression during AcMNPV infection. It provided a new insight for the understanding virus-host interaction mechanism.

  4. Teucrium pruinosum var. aksarayense var. nov. (Lamiaceae from Central Anatolia, Turkey

    Directory of Open Access Journals (Sweden)

    Muhittin Dinç

    2016-06-01

    Full Text Available Teucrium pruinosum var. aksarayense M. Dinç & S. Doğu (Lamiaceae, a new variety from Aksaray in Central Anatolia, is described and illustrated. The new variety is similar to the typical one in its calyx teeth uncinate at tip and subequal to the tube with conspicious midvein. It is readily distinguished from var. pruinosum by its general appearance, indumentum, and floral organ pigmentation. The map showing the distributions of the varieties was given.

  5. Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

    Directory of Open Access Journals (Sweden)

    Jaime Buitrago

    2017-01-01

    Full Text Available Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN with exogenous multi-variable input (NARX. The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. The New England electrical load data are used to train and validate the forecast prediction.

  6. Generalized Spatial Two Stage Least Squares Estimation of Spatial Autoregressive Models with Autoregressive Disturbances in the Presence of Endogenous Regressors and Many Instruments

    Directory of Open Access Journals (Sweden)

    Fei Jin

    2013-05-01

    Full Text Available This paper studies the generalized spatial two stage least squares (GS2SLS estimation of spatial autoregressive models with autoregressive disturbances when there are endogenous regressors with many valid instruments. Using many instruments may improve the efficiency of estimators asymptotically, but the bias might be large in finite samples, making the inference inaccurate. We consider the case that the number of instruments K increases with, but at a rate slower than, the sample size, and derive the approximate mean square errors (MSE that account for the trade-offs between the bias and variance, for both the GS2SLS estimator and a bias-corrected GS2SLS estimator. A criterion function for the optimal K selection can be based on the approximate MSEs. Monte Carlo experiments are provided to show the performance of our procedure of choosing K.

  7. Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

    Directory of Open Access Journals (Sweden)

    Lili Li

    2016-01-01

    Full Text Available We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7 and China. The quantile autoregression model (QAR enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

  8. A VAR Analysis of Kenya’s Monetary Policy Transmission Mechanism; How Does the Central Bank’s REPO Rate Affect the Economy?

    OpenAIRE

    Kevin C Cheng

    2006-01-01

    This paper examines the impact of a monetary policy shock on output, prices, and the nominal effective exchange rate for Kenya using data during 1997–2005. Based on techniques commonly used in the vector autoregression literature, the main results suggest that an exogenous increase in the short-term interest rate tends to be followed by a decline in prices and appreciation in the nominal exchange rate, but has insignificant impact on output. Moreover, the paper finds that variations in the sh...

  9. Autoregressive Processes in Homogenization of GNSS Tropospheric Data

    Science.gov (United States)

    Klos, A.; Bogusz, J.; Teferle, F. N.; Bock, O.; Pottiaux, E.; Van Malderen, R.

    2016-12-01

    Offsets due to changes in hardware equipment or any other artificial event are all a subject of a task of homogenization of tropospheric data estimated within a processing of Global Navigation Satellite System (GNSS) observables. This task is aimed at identifying exact epochs of offsets and estimate their magnitudes since they may artificially under- or over-estimate trend and its uncertainty delivered from tropospheric data and used in climate studies. In this research, we analysed a common data set of differences of Integrated Water Vapour (IWV) from GPS and ERA-Interim (1995-2010) provided for a homogenization group working within ES1206 COST Action GNSS4SWEC. We analysed daily IWV records of GPS and ERA-Interim in terms of trend, seasonal terms and noise model with Maximum Likelihood Estimation in Hector software. We found that this data has a character of autoregressive process (AR). Basing on this analysis, we performed Monte Carlo simulations of 25 years long data with two different noise types: white as well as combination of white and autoregressive and also added few strictly defined offsets. This synthetic data set of exactly the same character as IWV from GPS and ERA-Interim was then subjected to a task of manual and automatic/statistical homogenization. We made blind tests and detected possible epochs of offsets manually. We found that simulated offsets were easily detected in series with white noise, no influence of seasonal signal was noticed. The autoregressive series were much more problematic when offsets had to be determined. We found few epochs, for which no offset was simulated. This was mainly due to strong autocorrelation of data, which brings an artificial trend within. Due to regime-like behaviour of AR it is difficult for statistical methods to properly detect epochs of offsets, which was previously reported by climatologists.

  10. Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

    Science.gov (United States)

    Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

    2018-01-01

    Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

  11. Methodology for the AutoRegressive Planet Search (ARPS) Project

    Science.gov (United States)

    Feigelson, Eric; Caceres, Gabriel; ARPS Collaboration

    2018-01-01

    The detection of periodic signals of transiting exoplanets is often impeded by the presence of aperiodic photometric variations. This variability is intrinsic to the host star in space-based observations (typically arising from magnetic activity) and from observational conditions in ground-based observations. The most common statistical procedures to remove stellar variations are nonparametric, such as wavelet decomposition or Gaussian Processes regression. However, many stars display variability with autoregressive properties, wherein later flux values are correlated with previous ones. Providing the time series is evenly spaced, parametric autoregressive models can prove very effective. Here we present the methodology of the Autoregessive Planet Search (ARPS) project which uses Autoregressive Integrated Moving Average (ARIMA) models to treat a wide variety of stochastic short-memory processes, as well as nonstationarity. Additionally, we introduce a planet-search algorithm to detect periodic transits in the time-series residuals after application of ARIMA models. Our matched-filter algorithm, the Transit Comb Filter (TCF), replaces the traditional box-fitting step. We construct a periodogram based on the TCF to concentrate the signal of these periodic spikes. Various features of the original light curves, the ARIMA fits, the TCF periodograms, and folded light curves at peaks of the TCF periodogram can then be collected to provide constraints for planet detection. These features provide input into a multivariate classifier when a training set is available. The ARPS procedure has been applied NASA's Kepler mission observations of ~200,000 stars (Caceres, Dissertation Talk, this meeting) and will be applied in the future to other datasets.

  12. Hvem var morderen?

    DEFF Research Database (Denmark)

    Andersen, Lene Vinther

    2014-01-01

    Folkemindesamleren og forfatteren Helene Strange (1874-1943) skrev flere gange om et giftmord på en præst på Nordfalster i 1755. Hun satte spørgsmålstegn ved højesteretsdommen og hævdede, at en uskyldig pige blev dømt, mens den virkelige morder slap fri. Det var folkets uskrevne dom, som i over...... hundrede år var blevet fortalt mundtligt videre på egnen, og hun forsøgte – med forskellige midler – at få bragt denne version af historien frem i offentligheden....

  13. Housing market volatility in the OECD area: Evidence from VAR based return decompositions

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard

    . For the majority of countries news about future returns is the main driver, and both real interest rates and risk premia play an important role in accounting for housing market volatility. Bivariate cross-country correlations and principal components analyses indicate that part of the return movements have......Vector-autoregressive models are used to decompose housing returns in 18 OECD countries into cash ‡ow (rent) news and discount rate (return) news. Only for two countries - Germany and Ireland - do changing expectations of future rents play a dominating role in explaining housing return volatility...... a common factor among the majority of countries. However, in a minority of countries (Germany, Japan, and the Netherlands) return movements have been basically unrelated to return movements in other countries....

  14. Identification and Characterization of the Spodoptera Su(var) 3-9 Histone H3K9 trimethyltransferase and Its Effect in AcMNPV Infection

    Science.gov (United States)

    Li, Binbin; Li, Sisi; Yin, Juan; Zhong, Jiang

    2013-01-01

    Histone H3-lysine9 (H3K9) trimethyltransferase gene Su(var) 3-9 was cloned and identified in three Spodoptera insects, Spodoptera frugiperda ( S . frugiperda ), S . exigua and S . litura . Sequence analysis showed that Spodoptera Su(var) 3-9 is highly conserved evolutionarily. Su(var) 3-9 protein was found to be localized in the nucleus in Sf9 cells, and interact with histone H3, and the heterochromatin protein 1a (HP1a) and HP1b. A dose-dependent enzymatic activity was found at both 27 °C and 37 °C in vitro, with higher activity at 27 °C. Addition of specific inhibitor chaetocin resulted in decreased histone methylation level and host chromatin relaxation. In contrast, overexpression of Su(var) 3-9 caused increased histone methylation level and cellular genome compaction. In AcMNV-infected Sf9 cells, the transcription of Su(var) 3-9 increased at late time of infection, although the mRNA levels of most cellular genes decreased. Pre-treatment of Sf9 cells with chaetocin speeded up viral DNA replication, and increased the transcription level of a variety of virus genes, whereas in Sf9 cells pre-transformed with Su(var) 3-9 expression vector, viral DNA replication slow down slightly. These findings suggest that Su(var) 3-9 might participate in the viral genes expression an genome replication repression during AcMNPV infection. It provided a new insight for the understanding virus–host interaction mechanism. PMID:23894480

  15. Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)

    DEFF Research Database (Denmark)

    Agosto, Arianna; Cavaliere, Guiseppe; Kristensen, Dennis

    We develop a class of Poisson autoregressive models with additional covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used...

  16. The Effects of Remittances on Inflation: Evidence from Bangladesh

    Directory of Open Access Journals (Sweden)

    Z. S. Khan

    2013-12-01

    Full Text Available Like many developing countries, remittances are relatively larger capital inflows in Bangladesh in the recent years. Hence, understanding the impact of remittances on the macroeconomic variables such as inflation is essential for the policy makers of the recipient economy. Incorporating remittances as an exogenous variable to the standard inflation function, this paper verifies how it affects the inflation rate in Bangladesh in the 1972-2010 periods. Applying Vector Autoregressive (VAR techniques, the empirical results find that a one percent increase in remittances inflows increases inflation rate by 2.48 percent in the long run, whereas no significant relationship is evident between these two variables in the short-run in Bangladesh.

  17. The Vibrio cholerae var regulon encodes a metallo-β-lactamase and an antibiotic efflux pump, which are regulated by VarR, a LysR-type transcription factor.

    Directory of Open Access Journals (Sweden)

    Hong-Ting Victor Lin

    Full Text Available The genome sequence of V. cholerae O1 Biovar Eltor strain N16961 has revealed a putative antibiotic resistance (var regulon that is predicted to encode a transcriptional activator (VarR, which is divergently transcribed relative to the putative resistance genes for both a metallo-β-lactamase (VarG and an antibiotic efflux-pump (VarABCDEF. We sought to test whether these genes could confer antibiotic resistance and are organised as a regulon under the control of VarR. VarG was overexpressed and purified and shown to have β-lactamase activity against penicillins, cephalosporins and carbapenems, having the highest activity against meropenem. The expression of VarABCDEF in the Escherichia coli (ΔacrAB strain KAM3 conferred resistance to a range of drugs, but most significant resistance was to the macrolide spiramycin. A gel-shift analysis was used to determine if VarR bound to the promoter regions of the resistance genes. Consistent with the regulation of these resistance genes, VarR binds to three distinct intergenic regions, varRG, varGA and varBC located upstream and adjacent to varG, varA and varC, respectively. VarR can act as a repressor at the varRG promoter region; whilst this repression was relieved upon addition of β-lactams, these did not dissociate the VarR/varRG-DNA complex, indicating that the de-repression of varR by β-lactams is indirect. Considering that the genomic arrangement of VarR-VarG is strikingly similar to that of AmpR-AmpC system, it is possible that V. cholerae has evolved a system for resistance to the newer β-lactams that would prove more beneficial to the bacterium in light of current selective pressures.

  18. VaR Methodology Application for Banking Currency Portfolios

    Directory of Open Access Journals (Sweden)

    Daniel Armeanu

    2007-02-01

    Full Text Available VaR has become the standard measure that financial analysts use to quantify market risk. VaR measures can have many applications, such as in risk management, to evaluate the performance of risk takers and for regulatory requirements, and hence it is very important to develop methodologies that provide accurate estimates. In particular, the Basel Committee on Banking Supervision at the Bank for International Settlements imposes to financial institutions such as banks and investment firms to meet capital requirements based on VaR estimates. In this paper we determine VaR for a banking currency portfolio and respect rules of National Bank of Romania regarding VaR report.

  19. Estimation of the order of an autoregressive time series: a Bayesian approach

    International Nuclear Information System (INIS)

    Robb, L.J.

    1980-01-01

    Finite-order autoregressive models for time series are often used for prediction and other inferences. Given the order of the model, the parameters of the models can be estimated by least-squares, maximum-likelihood, or Yule-Walker method. The basic problem is estimating the order of the model. The problem of autoregressive order estimation is placed in a Bayesian framework. This approach illustrates how the Bayesian method brings the numerous aspects of the problem together into a coherent structure. A joint prior probability density is proposed for the order, the partial autocorrelation coefficients, and the variance; and the marginal posterior probability distribution for the order, given the data, is obtained. It is noted that the value with maximum posterior probability is the Bayes estimate of the order with respect to a particular loss function. The asymptotic posterior distribution of the order is also given. In conclusion, Wolfer's sunspot data as well as simulated data corresponding to several autoregressive models are analyzed according to Akaike's method and the Bayesian method. Both methods are observed to perform quite well, although the Bayesian method was clearly superior, in most cases

  20. Conditional co-movement and dynamic interactions: US and BRIC equity markets

    Directory of Open Access Journals (Sweden)

    Singh Amanjot

    2017-01-01

    Full Text Available The present study attempts to capture conditional or time-varying co-movement and dynamic interactions between the US and BRIC (Brazil, Russia, India, and China equity markets across the sample period 2004 to 2014 by employing diverse econometric models. The sample period is further divided into three different sub-periods concerning the US financial crisis period, viz. pre-crisis, crisis, and post-crisis periods. The vector autoregression- dynamic conditional correlation-multivariate asymmetric generalized autoregressive conditional heteroskedastic [VAR-DCC-MVAGARCH (1.1] model and Toda-Yamamoto’s (1995 Granger causality tests are employed for the purpose of overall analysis in a multivariate framework. The results report the existence of time-varying co-movement between the US and BRIC equity markets, whereby co-movement between the US and Brazilian markets is found to be the highest, followed by the Russian, Indian, and Chinese equity markets. Dynamic interactions are also registered between the respective US/BRIC comovements during different sub-periods. The results have important implications for market participants and policymakers.

  1. [Physiological characteristics of Pinus densiflora var. zhangwuensis and Pinus sylvestris var. mongolica seedlings on sandy lands under salt-alkali stresses].

    Science.gov (United States)

    Meng, Peng; Li, Yu-Ling; Zhang, Bai-xi

    2013-02-01

    For the popularization of Pinus densiflora var. zhangwuensis, a new afforestation tree species on the desertified and salinized-alkalized lands in Northern China, and to evaluate the salinity-alkalinity tolerance of the tree species and to better understand the tolerance mechanisms, a pot experiment with 4-year old P. densiflora var. zhangwuensis and P. sylvestris var. mongolica was conducted to study their seedlings growth and physiological and biochemical indices under the effects of three types salt (NaCl, Na2CO3, and NaHCO3 ) stresses and of alkali (NaOH) stress. Under the salt-alkali stresses, the injury level of P. densiflora var. zhangwuensis was lower, and the root tolerance index was higher. The leaf catalase (CAT) activity increased significantly by 22. 6 times at the most, as compared with the control; the leaf malondialdehyde (MDA) content had no significant increase; the leaf chlorophyll (Chl) content had a smaller decrement; and the leaf water content (LWC) increased slightly. P. sylvestris var. mongolica responded differently to the salt-alkali stresses. Its leaf CAT activity had less change, MDA content increased significantly, Chl content had significant decrease, and LWC decreased slightly. It was suggested that P. densi-flora var. zhangwuensis had a greater salinity-alkalinity tolerance than P. sylvestris var. mongolica. The higher iron concentration in P. densiflora var. zhangwuensis needles enhanced the CAT activity and Chl content, whereas the higher concentrations of zinc and copper were associated with the stronger salinity-alkalinity tolerance.

  2. dbVar

    Data.gov (United States)

    U.S. Department of Health & Human Services — dbVar is a database of genomic structural variation. It accepts data from all species and includes clinical data. It can accept diverse types of events, including...

  3. Seasonal Forecasting of Agriculture Gross Domestic Production in Iran: Application of Periodic Autoregressive Model

    Directory of Open Access Journals (Sweden)

    Mohammad Ghahremanzadeh

    2014-06-01

    Full Text Available Agriculture as one of the major economic sectors of Iran, has an important role in Gross Domestic Production by providing about 14% of GDP. This study attempts to forecast the value of the agriculture GDP using Periodic Autoregressive model (PAR, as the new seasonal time series techniques. To address this aim, the quarterly data were collected from March 1988 to July 1989. The collected data was firstly analyzed using periodic unit root test Franses & Paap (2004. The analysis found non-periodic unit root in the seasonal data. Second, periodic seasonal behavior (Boswijk & Franses, 1996 was examined. The results showed that periodic autoregressive model fits agriculture GDP well. This makes an accurate forecast of agriculture GDP possible. Using the estimated model, the future value of quarter agricultural GDP from March 2011 to July 2012was forecasted. With consideration to the fair fit of this model with agricultural GDP, It is recommended to use periodic autoregressive model for the future studies.

  4. Forecasting performance of smooth transition autoregressive (STAR model on travel and leisure stock index

    Directory of Open Access Journals (Sweden)

    Usman M. Umer

    2018-06-01

    Full Text Available Travel and leisure recorded a consecutive robust growth and become among the fastest economic sectors in the world. Various forecasting models are proposed by researchers that serve as an early recommendation for investors and policy makers. Numerous studies proposed distinct forecasting models to predict the dynamics of this sector and provide early recommendation for investors and policy makers. In this paper, we compare the performance of smooth transition autoregressive (STAR and linear autoregressive (AR models using monthly returns of Turkey and FTSE travel and leisure index from April 1997 to August 2016. MSCI world index used as a proxy of the overall market. The result shows that nonlinear LSTAR model cannot improve the out-of-sample forecast of linear AR model. This finding demonstrates little to be gained from using LSTAR model in the prediction of travel and leisure stock index. Keywords: Nonlinear time-series, Out-of-sample forecasting, Smooth transition autoregressive, Travel and leisure

  5. Paulus var kristendommens Lenin

    DEFF Research Database (Denmark)

    Thyssen, Ole

    2017-01-01

    En af Luthers inspirationskilder var Paulus, hvis løsning på lokale problemer fik globale konsekvenser. Han trak en skarp grænse mellem det snavsede kød og den rene sjæl og mellem vantro og tro.......En af Luthers inspirationskilder var Paulus, hvis løsning på lokale problemer fik globale konsekvenser. Han trak en skarp grænse mellem det snavsede kød og den rene sjæl og mellem vantro og tro....

  6. B. oleracea var. capitata monosomic and disomic alien

    Indian Academy of Sciences (India)

    Five monosomic alien addition lines (MAALs) of Brassica rapa ssp. pekinensis – B. oleracea var. capitata were obtained by hybridization and backcrossing between B. rapa ssp. pekinensis (female parent) and B. oleracea var. capitata. The alien linkage groups were identified using 42 B. oleracea var. capitata linkage ...

  7. A fractionally cointegrated VAR analysis of price discovery in commodity futures markets

    DEFF Research Database (Denmark)

    Dolatabadi, Sepideh; Nielsen, Morten Ørregaard; Xu, Ke

    straightforward examination of the adjustment coefficients. In our empirical analysis we use the data from Figuerola-Ferretti and Gonzalo (2010), who conduct a similar analysis using the usual (non-fractional) CVAR model. Our first finding is that, for all markets except copper, the fractional integration......In this paper we apply the recently developed fractionally cointegrated vector autoregressive (FCVAR) model to analyze price discovery in the spot and futures markets for five non-ferrous metals (aluminium, copper, lead, nickel, and zinc). The FCVAR model allows for long memory (fractional...... to the results from the non-fractional model, we find slightly more evidence of price discovery in the spot market. Specifically, using standard likelihood ratio tests, we do not reject the hypothesis that price discovery takes place exclusively in the spot (futures) market for copper, lead, and zinc (aluminium...

  8. Da Danmark var en slavenation

    DEFF Research Database (Denmark)

    Peters, Rikke Louise Alberg; Brunbech, Peter Johan Yding; Poulsen, Jens Aage

    I mere end 250 år var Danmark en stor kolonimagt. Skt. Jan, Skt. Thomas og Skt. Croix, eller U.S. Virgin Islands, som de kaldes i dag, var danske kolonier, hvor der bl.a. blev dyrket sukkerrør og bomuld. Det hårde arbejde blev udført af slaver, som man fra slutningen af 1600-tallet begyndte at tr...

  9. ESTIMASI NILAI VaR PORTOFOLIO MENGGUNAKAN FUNGSI ARCHIMEDEAN COPULA

    Directory of Open Access Journals (Sweden)

    AULIA ATIKA PRAWIBTA SUHARTO

    2017-01-01

    Full Text Available Value at Risk explains the magnitude of the worst losses occurred in financial products investments with a certain level of confidence and time interval. The purpose of this study is to estimate the VaR of portfolio using Archimedean Copula family. The methods for calculating the VaR are as follows: (1 calculating the stock return; (2 calculating descriptive statistics of return; (3 checking for the nature of autocorrelation and heteroscedasticity effects on stock return data; (4 checking for the presence of extreme value by using Pareto tail; (5 estimating the parameters of Achimedean Copula family; (6 conducting simulations of Archimedean Copula; (7 estimating the value of the stock portfolio VaR. This study uses the closing price of TLKM and GGRM. At 90% the VaR obtained using Clayton, Gumbel, Frank copulas are 0.9562%, 1.0189%, 0.9827% respectively. At 95% the VaR obtained using Clayton, Gumbel, Frank copulas are 1.2930%, 1.2522%, 1.3152% respectively. At 99% the VaR obtained using Clayton, Gumbel, Frank copulas are 2.0327%, 1.9164%, is 1.8678% respectively. In conclusion estimation of VaR using Clayton copula yields the highest VaR.

  10. Monthly streamflow forecasting with auto-regressive integrated moving average

    Science.gov (United States)

    Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

    2017-09-01

    Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

  11. Over de verspreiding binnen Nederland van Bidens connata var. fallax (Warnst.) Sherf en var. anomala Farw

    NARCIS (Netherlands)

    Ballintijn, Koos (J.) F.

    1997-01-01

    On the basis of recent observations and study of herbarium material it might tentatively be concluded that var. anomala (with erecto-patent barb hairs on achenes as well as on the bristles) is becoming more common since 1954 and might be locally replacing the hitherto more common var. fallax (with

  12. A note on intrinsic conditional autoregressive models for disconnected graphs

    KAUST Repository

    Freni-Sterrantino, Anna

    2018-05-23

    In this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples, on disease mapping.

  13. A note on intrinsic conditional autoregressive models for disconnected graphs

    KAUST Repository

    Freni-Sterrantino, Anna; Ventrucci, Massimo; Rue, Haavard

    2018-01-01

    In this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples, on disease mapping.

  14. Hybrid VAR compensator with improved efficiency

    Directory of Open Access Journals (Sweden)

    V. V. Burlaka

    2015-03-01

    Full Text Available In modern electrical networks thyristor-switched capacitors (TSC are most used devices for VAR compensation. These devices don’t contain rotating parts and mechanical contacts, provide a stepwise control of reactive power and no generation of harmonics to the network. However, with the help of TSC it’s not possible to ensure smooth control of reactive power and capacitor banks (CB are exposed to the negative impact of higher harmonic components of the network voltage. Hybrid VAR compensator don’t have such drawbacks. It consists of active filter (AF and capacitor bank with discrete regulation. The main drawback of such systems is the necessity of accessing all six terminals of CB, while most of them are manufactured with three terminals, internally delta-connected. In the article, the topology and control system of hybrid VAR compensator free from beforementioned drawback, is proposed. The control system provides operating modes of overcompensation or undercompensation reactive power. VAR distribution regulator performs redistribution of reactive power between active filter and capacitor banks with the condition to minimize active filter’s power. Scheme of the hybrid VAR compensator, which includes a three-phase three-terminal delta-connected capacitor banks, is shown. Proposed approach allows to provide smooth control of reactive power, isolate the capacitor bank from harmonic currents and use a more effective low-voltage power components

  15. Does health promote economic growth? Portuguese case study: from dictatorship to full democracy.

    Science.gov (United States)

    Morgado, Sónia Maria Aniceto

    2014-07-01

    This paper revisits the debate on health and economic growth (Deaton in J Econ Lit 51:113-158, 2003) focusing on the Portuguese case by testing the relationship between growth and health. We test Portuguese insights, using time series data from 1960 to 2005, taking into account different variables (life expectancy, labour, capital, infant mortality) and considering the years that included major events on the political scene, such as the dictatorship and a closed economy (1960-1974), a revolution (1974) and full democracy and an open economy (1975-2005), factors that influence major economic, cultural, social and politic indicators. Therefore the analysis is carried out adopting Lucas' (J Monet Econ 22(1):3-42, 1988) endogenous growth model that considers human capital as one factor of production, it adopts a VAR (vector autoregressive) model to test the causality between growth and health. Estimates based on the VAR seem to confirm that economic growth influences the health process, but health does not promote growth, during the period under study.

  16. Non performing loans (NPLs) in a crisis economy: Long-run equilibrium analysis with a real time VEC model for Greece (2001-2015)

    Science.gov (United States)

    Konstantakis, Konstantinos N.; Michaelides, Panayotis G.; Vouldis, Angelos T.

    2016-06-01

    As a result of domestic and international factors, the Greek economy faced a severe crisis which is directly comparable only to the Great Recession. In this context, a prominent victim of this situation was the country's banking system. This paper attempts to shed light on the determining factors of non-performing loans in the Greek banking sector. The analysis presents empirical evidence from the Greek economy, using aggregate data on a quarterly basis, in the time period 2001-2015, fully capturing the recent recession. In this work, we use a relevant econometric framework based on a real time Vector Autoregressive (VAR)-Vector Error Correction (VEC) model, which captures the dynamic interdependencies among the variables used. Consistent with international evidence, the empirical findings show that both macroeconomic and financial factors have a significant impact on non-performing loans in the country. Meanwhile, the deteriorating credit quality feeds back into the economy leading to a self-reinforcing negative loop.

  17. STUDY REGARDING THE ASSESSMENT OF THE FINANCIAL STABILITY OF THE ECONOMIC ENTITIES

    Directory of Open Access Journals (Sweden)

    N. Baltes

    2016-11-01

    Full Text Available The research presents both theoretical and practicalthe evolution of the financial stability assessed through the solvency indicators, the real economic growth rate and the GDP deflator in the manufacturing companies from Romania, through the Vector Autoregression Model (VAR. The sample consists in 36 companies belonging to the manufacturing industry in Romania, listed on the Bucharest Stock Exchange, on the first and second category. The study is conducted during the period 2007-2014 and demonstrated the fact that a change in the real economic growth causes a positive change in the GDP deflator. Not lastly, the change of the real economic growth also determines a positive change of the patrimonial solvency, and a change in the GDP deflator produces a reduction of the patrimonial solvency.

  18. Vergi-Harcama Tartışması : Türkiye Örneği = The Tax-Spend Debate : The Case of Turkey

    Directory of Open Access Journals (Sweden)

    İhsan GÜNAYDIN

    2004-06-01

    Full Text Available This paper examines the short and long-run relationship between goverment revenues, expenditures, GNP and interest rates for Turkey for the period 1987:1-2003:3, using error correction model (ECM and the augmented vector autoregressive (VAR model developed in Toda-Yamamoto (1995. The results indicate that there is one long-run equilibrium relationship among the four variables, and the causal relationship flows unidirectionally from government revenues to expentitures both in the short and long-run, providing support for the tax-spend theory.The results further reveal that the unidirectional causal impact of revenues on expentitures is significantly negative as hypothesized by Buchanan and Wagner. Thus, higher taxes seem an optimal resolution to the budget deficits in Turkey.

  19. Gezi Parkı Olaylarının Türkiye Kredi Temerrüt Swapları (CDS Üzerine Etkisi (The Effects of Gezi Park Protests on Turkey’s Credit Default Swaps (CDS

    Directory of Open Access Journals (Sweden)

    Musa GÜN

    2016-03-01

    Full Text Available Credit default swap is also referred to as a credit derivative contract where the counterparty of the swap makes payments up until the maturity date of a financial contract. In this study, whether Gezi Park events which happened in 2013 are on a significant impact on Turkey credit default swap spread or not tested with the VAR(Vector Auto-Regressive method. In the analysis, investigated the long-term relationship with Johansen co-integration test and causality with Granger test. In addition, variance decomposition and impulse response analysis are performed. According to the results found significant correlations between Gezi Park events and CDS and also Eurobonds interest, the BIST 100 index, a basket of currencies with CDS spreads have been identified.

  20. Linkage Between External and Internal Imbalance – The Case of Serbia

    Directory of Open Access Journals (Sweden)

    Dejan Živkov

    2013-12-01

    Full Text Available After a while almost all transition and emerging countries that have entered into the process of economic reforms became attractive for foreign direct investments and foreign loans. Consequently, huge amount of capital inflow lead to the surpluses in the financial-capital account. Capital that has entered the system usually converts into the local currency and thus contributes to the growth of money supply in the system. However, high level of money supply leads to internal imbalances such as relatively high inflation and unstable exchange rate. In this paper we will try to give an answer to whether above described scenario is characteristic for Serbian transition economy. In this process we will use linear regression, vector auto-regression (VAR and error correction model.

  1. Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

    International Nuclear Information System (INIS)

    Chen, Kuilin; Yu, Jie

    2014-01-01

    Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

  2. Var der noget kapløb?

    DEFF Research Database (Denmark)

    Gimpel, Denise; Nielsen, Bent

    2006-01-01

    Hvorfor faldt Kina bagud i kapløbet med Vesten?« spørger David Favrholdt i sidste nummer af Weekendavisen. Var der overhovedet noget kapløb? Forudsætter et kapløb ikke, at man har et fælles mål? Spørgsmålet implicerer, at Vesten har vundet og indplacerer samtidig klodens øvrige kulturer i forhold....... Som en af 1900-tallets største sinologer A. C. Graham skriver i sin bog Disputers of the Tao (La Salle, Ill., 1989) var den videnskabelige revolution »en unik og kompleks begivenhed, som var afhængig af en mangfoldighed af sociale og andre betingelser, herunder et sammenfald af opdagelser (græske......, indiske, kinesiske, arabiske, næsten ingen romerske) koncentreret om kombinationen af indiske tal og aritmetik og græsk logik og geometri« (s. 317). En unik begivenhed, som er forekommet én gang i verdenshistorien. Det giver derfor ingen mening at spørge, hvorfor det ikke skete andre steder. Hvis det var...

  3. Damage and noise sensitivity evaluation of autoregressive features extracted from structure vibration

    International Nuclear Information System (INIS)

    Yao, Ruigen; Pakzad, Shamim N

    2014-01-01

    In the past few decades many types of structural damage indices based on structural health monitoring signals have been proposed, requiring performance evaluation and comparison studies on these indices in a quantitative manner. One tool to help accomplish this objective is analytical sensitivity analysis, which has been successfully used to evaluate the influences of system operational parameters on observable characteristics in many fields of study. In this paper, the sensitivity expressions of two damage features, namely the Mahalanobis distance of autoregressive coefficients and the Cosh distance of autoregressive spectra, will be derived with respect to both structural damage and measurement noise level. The effectiveness of the proposed methods is illustrated in a numerical case study on a 10-DOF system, where their results are compared with those from direct simulation and theoretical calculation. (paper)

  4. Improved inference on cointegrating vectors in the presence of a near unit root using adjusted quantiles

    DEFF Research Database (Denmark)

    Franchi, Massimo; Johansen, Søren

    2017-01-01

    It is well known that inference on the cointegrating relations in a vector autoregression (CVAR) is difficult in the presence of a near unit root. The test for a given cointegration vector can have rejection probabilities under the null, which vary from the nominal size to more than 90%. This paper...... formulates a CVAR model allowing for many near unit roots and analyses the asymptotic properties of the Gaussian maximum likelihood estimator. Then a critical value adjustment suggested by McCloskey for the test on the cointegrating relations is implemented, and it is found by simulation that it eliminates...... size distortions and has reasonable power for moderate values of the near unit root parameter. The findings are illustrated with an analysis of a number of different bivariate DGPs....

  5. Improved inference on cointegrating vectors in the presence of a near unit root using adjusted quantiles

    DEFF Research Database (Denmark)

    Franchi, Massimo; Johansen, Søren

    It is well known that inference on the cointegrating relations in a vector autoregression (CVAR) is difficult in the presence of a near unit root. The test for a given cointegration vector can have rejection probabilities under the null, which vary from the nominal size to more than 90%. This paper...... formulates a CVAR model allowing for many near unit roots and analyses the asymptotic properties of the Gaussian maximum likelihood estimator. Then a critical value adjustment suggested by McCloskey for the test on the cointegrating relations is implemented, and it is found by simulation that it eliminates...... size distortions and has reasonable power for moderate values of the near unit root parameter. The findings are illustrated with an analysis of a number of different bivariate DGPs....

  6. Multivariate Autoregressive Model Based Heart Motion Prediction Approach for Beating Heart Surgery

    Directory of Open Access Journals (Sweden)

    Fan Liang

    2013-02-01

    Full Text Available A robotic tool can enable a surgeon to conduct off-pump coronary artery graft bypass surgery on a beating heart. The robotic tool actively alleviates the relative motion between the point of interest (POI on the heart surface and the surgical tool and allows the surgeon to operate as if the heart were stationary. Since the beating heart's motion is relatively high-band, with nonlinear and nonstationary characteristics, it is difficult to follow. Thus, precise beating heart motion prediction is necessary for the tracking control procedure during the surgery. In the research presented here, we first observe that Electrocardiography (ECG signal contains the causal phase information on heart motion and non-stationary heart rate dynamic variations. Then, we investigate the relationship between ECG signal and beating heart motion using Granger Causality Analysis, which describes the feasibility of the improved prediction of heart motion. Next, we propose a nonlinear time-varying multivariate vector autoregressive (MVAR model based adaptive prediction method. In this model, the significant correlation between ECG and heart motion enables the improvement of the prediction of sharp changes in heart motion and the approximation of the motion with sufficient detail. Dual Kalman Filters (DKF estimate the states and parameters of the model, respectively. Last, we evaluate the proposed algorithm through comparative experiments using the two sets of collected vivo data.

  7. Granger Causalities Between Interest Rate, Price Level, Money Supply and Real Gdp in the Czech Republic

    Directory of Open Access Journals (Sweden)

    Tomáš Urbanovský

    2017-01-01

    Full Text Available The main aim of this paper is to investigate relationships between selected macroeconomic variables – interest rate, price level, money supply and real GDP – in the Czech Republic in order to find out definite implications of its interactions and give recommendations to macroeconomic policy authorities. Two implemented vector autoregression models with different lag length reached slightly different conclusions. VAR(1 suggests that three pairs of Granger causality exist, in particular between price level and interest rate, between real GDP and interest rate and between real GDP and price level. VAR(2 uncovered two more pairs of Granger causality between money supply and interest rate and between money supply and price level. Despite better prediction power of VAR(2 in case of money supply, low correlation coefficient comprising variable money supply raises doubts about the factual existence of causality between money supply and other variables. However, both models allow forecasting the direction of change in case of variables interest rate and real GDP with the same success rate nearly 82 %. Both VARs also agreed that interest rate could be changed by change of price level and that interest rate could be changed by change of real GDP. These conclusions represent potential recommendations to macroeconomic policy authorities. For the purpose of further research, exchange rate variable will be included in the model instead of interest rate, because effect of interest rate turned out to be limited in times of weakened state of Czech economy.

  8. CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Hansen, Lars Kai

    2004-01-01

    We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least square...... estimation. We demonstrate the method on synthetic data and finally separate speech and music in a real room recording....

  9. Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

    Science.gov (United States)

    Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

    2014-01-01

    Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

  10. Anti-adipogenic effects of extracts of Ficus deltoidea var. deltoidea and var. angustifolia on 3T3-L1 adipocytes.

    Science.gov (United States)

    Woon, Shiau Mei; Seng, Yew Wei; Ling, Anna Pick Kiong; Chye, Soi Moi; Koh, Rhun Yian

    2014-03-01

    This study examined the anti-adipogenic effects of extracts of Ficus deltoidea var. deltoidia and var. angustifolia, a natural slimming aid, on 3T3-L1 adipocytes. Methanol and water extracts of leaves of the F. deltoidea varieties were analyzed to determine their total flavonoid content (TFC) and total phenolic content (TPC), respectively. The study was initiated by determining the maximum non-toxic dose (MNTD) of the methanol and water extracts for 3T3-L1 preadipocytes. Possible anti-adipogenic effects were then examined by treating 2-d post confluent 3T3-L1 preadipocytes with either methanol extract or water extract at MNTD and half MNTD (½MNTD), after which the preadipocytces were induced to form mature adipocytes. Visualisation and quantification of lipid content in mature adipocytes were carried out through oil red O staining and measurement of optical density (OD) at 520 nm, respectively. The TFCs of the methanol extracts were 1.36 and 1.97 g quercetin equivalents (QE)/100 g dry weight (DW), while the TPCs of the water extracts were 5.61 and 2.73 g gallic acid equivalents (GAE)/100 g DW for var. deltoidea and var. angustilofia, respectively. The MNTDs determined for methanol and water extracts were (300.0 ± 28.3) and (225.0 ± 21.2) µg/ml, respectively, for var. deltoidea, while much lower MNTDs [(60.0 ± 2.0) µg/ml for methanol extracts and (8.0 ± 1.0) µg/ml for water extracts] were recorded for var. angustifolia. Studies revealed that the methanol extracts of both varieties and the water extracts of var. angustifolia at either MNTD or ½MNTD significantly inhibited the maturation of preadipocytes. The inhibition of the formation of mature adipocytes indicated that leaf extracts of F. deltoidea could have potential anti-obesity effects.

  11. Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy

    Science.gov (United States)

    Mazzarella, Vincenzo; Maiello, Ida; Capozzi, Vincenzo; Budillon, Giorgio; Ferretti, Rossella

    2017-08-01

    This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. To evaluate the impact of the assimilation of reflectivity and radial velocity acquired from Monte Midia Doppler radar into the Weather Research Forecasting (WRF) model, the quantitative precipitation forecast (QPF) is used.The two methods are compared for a heavy rainfall event that occurred in central Italy on 14 September 2012 during the first Special Observation Period (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment) campaign. This event, characterized by a deep low pressure system over the Tyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions, where rainfall maxima reached more than 150 mm 24 h-1.To identify the best QPF, nine experiments are performed using 3D-Var and 4D-Var data assimilation techniques. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators: probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR). The assimilation of conventional observations with 4D-Var method improves the QPF compared to 3D-Var. In addition, the use of radar measurements in 4D-Var simulations enhances the performances of statistical scores for higher rainfall thresholds.

  12. VAR Methodology Used for Exchange Risk Measurement and Prevention

    Directory of Open Access Journals (Sweden)

    Florentina Balu

    2006-05-01

    Full Text Available In this article we discuss one of the modern risk measuring techniques Value-at-Risk (VaR. Currently central banks in major money centers, under the auspices of the BIS Basle Committee, adopt the VaR system to evaluate the market risk of their supervised banks. Banks regulators ask all commercial banks to report VaRs with their internal models. Value at risk (VaR is a powerful tool for assessing market risk, but it also imposes a challenge. Its power is its generality. Unlike market risk metrics such as the Greeks, duration and convexity, or beta, which are applicable to only certain asset categories or certain sources of market risk, VaR is general. It is based on the probability distribution for a portfolio’s market value. Value at Risk (VAR calculates the maximum loss expected (or worst case scenario on an investment, over a given time period and given a specified degree of confidence. There are three methods by which VaR can be calculated: the historical simulation, the variance-covariance method and the Monte Carlo simulation. The variance-covariance method is easiest because you need to estimate only two factors: average return and standard deviation. However, it assumes returns are well-behaved according to the symmetrical normal curve and that historical patterns will repeat into the future. The historical simulation improves on the accuracy of the VAR calculation, but requires more computational data; it also assumes that “past is prologue”. The Monte Carlo simulation is complex, but has the advantage of allowing users to tailor ideas about future patterns that depart from historical patterns.

  13. VAR Methodology Used for Exchange Risk Measurement and Prevention

    Directory of Open Access Journals (Sweden)

    Ion Stancu

    2006-03-01

    Full Text Available In this article we discuss one of the modern risk measuring techniques Value-at-Risk (VaR. Currently central banks in major money centers, under the auspices of the BIS Basle Committee, adopt the VaR system to evaluate the market risk of their supervised banks. Banks regulators ask all commercial banks to report VaRs with their internal models. Value at risk (VaR is a powerful tool for assessing market risk, but it also imposes a challenge. Its power is its generality. Unlike market risk metrics such as the Greeks, duration and convexity, or beta, which are applicable to only certain asset categories or certain sources of market risk, VaR is general. It is based on the probability distribution for a portfolio’s market value. Value at Risk (VAR calculates the maximum loss expected (or worst case scenario on an investment, over a given time period and given a specified degree of confidence. There are three methods by which VaR can be calculated: the historical simulation, the variance-covariance method and the Monte Carlo simulation. The variance-covariance method is easiest because you need to estimate only two factors: average return and standard deviation. However, it assumes returns are well-behaved according to the symmetrical normal curve and that historical patterns will repeat into the future. The historical simulation improves on the accuracy of the VAR calculation, but requires more computational data; it also assumes that “past is prologue”. The Monte Carlo simulation is complex, but has the advantage of allowing users to tailor ideas about future patterns that depart from historical patterns.

  14. Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input

    OpenAIRE

    Addo, Peter Martey

    2014-01-01

    This study defines a multivariate Self--Exciting Threshold Autoregressive with eXogenous input (MSETARX) models and present an estimation procedure for the parameters. The conditions for stationarity of the nonlinear MSETARX models is provided. In particular, the efficiency of an adaptive parameter estimation algorithm and LSE (least squares estimate) algorithm for this class of models is then provided via simulations.

  15. Morphological and genetic differences between Coptis japonica var. anemonifolia H. Ohba and Coptis japonica var. major Satake in Hokuriku area.

    Science.gov (United States)

    Kitamura, Masashi; Ando, Hirokazu; Sasaki, Yohei

    2018-03-01

    Coptis japonica is widely distributed in Japan, and its dried rhizome is a source of the domestic herbal medicine Coptidis Rhizoma ( Oren). There are three varieties of C. japonica, two of which, namely, C. japonica var. anemonifolia and C. japonica var. major, are important as sources of traditional medicines. Coptis japonica var. anemonifolia and C. japonica var. major are distinguishable on the basis of their ternate or biternate compound leaves, respectively. In the Hokuriku area, where both C. japonica var. anemonifolia and C. japonica var. major grow naturally, some individual plants cannot be identified unambiguously on the basis of leaf morphology because changes in leaf morphology may occur due to intra-variety variation or crossbreeding between the two varieties. In addition, genetic differences between the two varieties have remained unclear. In this study, we employed new genetic and morphological classification approaches to discriminate between the two varieties. Based on the single nucleotide polymorphisms of the tetrahydroberberine oxidase gene, we found four conserved SNPs between the two varieties and were able to classify C. japonica into two varieties and crossbreeds. Furthermore, we introduced a new leaf type index based on the overall degree of leaflet dissection calculated by surface area of a leaflet and length of leaflet margin and petiolule. Using our new index we were able to discriminate between the two varieties and their crossbreeds more accurately than is possible with the conventional discrimination method. Our genetic and morphological classification methods may be used as novel benchmarks to discriminate between the two varieties and their crossbreeds.

  16. Improved Inference on Cointegrating Vectors in the Presence of a near Unit Root Using Adjusted Quantiles

    DEFF Research Database (Denmark)

    Franchi, Massimo; Johansen, Søren

    2017-01-01

    It is well known that inference on the cointegrating relations in a vector autoregression (CVAR) is difficult in the presence of a near unit root. The test for a given cointegration vector can have rejection probabilities under the null, which vary from the nominal size to more than 90%. This paper...... formulates a CVAR model allowing for multiple near unit roots and analyses the asymptotic properties of the Gaussian maximum likelihood estimator. Then two critical value adjustments suggested by McCloskey (2017) for the test on the cointegrating relations are implemented for the model with a single near...... unit root, and it is found by simulation that they eliminate the serious size distortions, with a reasonable power for moderate values of the near unit root parameter. The findings are illustrated with an analysis of a number of different bivariate DGPs....

  17. Foliar flavonoids from Tanacetum vulgare var. boreale and their geographical variation.

    Science.gov (United States)

    Uehara, Ayumi; Akiyama, Shinobu; Iwashina, Tsukasa

    2015-03-01

    Foliar flavonoids of Tanacetum vulgare var. boreale were isolated. Eight flavonoid glycosides, 7-O-glucosides of apigenin, luteolin, scutellarein and 6- hydroxyluteolin, and 7-O-glucuronides of apigenin, luteolin, chrysoeriol and eriodictyol were identified. Moreover, eight flavonoid aglycones, apigenin, luteolin, hispidulin, nepetin, eupatilin, jaceosidin, pectolinarigenin and axillarin were also isolated and identified. The flavonoid composition of two varieties of T. vulgare, i.e. var. boreale and var. vulgare, were compared. All samples of var. boreale and one sample of var. vulgare had the same flavonoid pattern, and could be distinguished from almost all the samples of var. vulgare. Thus, the occurrence of chemotypes, which are characterized by either the presence or absence of scutellarein 7-O-glucoside, eriodictyol 7-O-glucuronide and pectolinarigenin was shown in T. vulgare sensu lato.

  18. Activation and clustering of a Plasmodium falciparum var gene are affected by subtelomeric sequences.

    Science.gov (United States)

    Duffy, Michael F; Tang, Jingyi; Sumardy, Fransisca; Nguyen, Hanh H T; Selvarajah, Shamista A; Josling, Gabrielle A; Day, Karen P; Petter, Michaela; Brown, Graham V

    2017-01-01

    The Plasmodium falciparum var multigene family encodes the cytoadhesive, variant antigen PfEMP1. P. falciparum antigenic variation and cytoadhesion specificity are controlled by epigenetic switching between the single, or few, simultaneously expressed var genes. Most var genes are maintained in perinuclear clusters of heterochromatic telomeres. The active var gene(s) occupy a single, perinuclear var expression site. It is unresolved whether the var expression site forms in situ at a telomeric cluster or whether it is an extant compartment to which single chromosomes travel, thus controlling var switching. Here we show that transcription of a var gene did not require decreased colocalisation with clusters of telomeres, supporting var expression site formation in situ. However following recombination within adjacent subtelomeric sequences, the same var gene was persistently activated and did colocalise less with telomeric clusters. Thus, participation in stable, heterochromatic, telomere clusters and var switching are independent but are both affected by subtelomeric sequences. The var expression site colocalised with the euchromatic mark H3K27ac to a greater extent than it did with heterochromatic H3K9me3. H3K27ac was enriched within the active var gene promoter even when the var gene was transiently repressed in mature parasites and thus H3K27ac may contribute to var gene epigenetic memory. © 2016 Federation of European Biochemical Societies.

  19. Chain binomial models and binomial autoregressive processes.

    Science.gov (United States)

    Weiss, Christian H; Pollett, Philip K

    2012-09-01

    We establish a connection between a class of chain-binomial models of use in ecology and epidemiology and binomial autoregressive (AR) processes. New results are obtained for the latter, including expressions for the lag-conditional distribution and related quantities. We focus on two types of chain-binomial model, extinction-colonization and colonization-extinction models, and present two approaches to parameter estimation. The asymptotic distributions of the resulting estimators are studied, as well as their finite-sample performance, and we give an application to real data. A connection is made with standard AR models, which also has implications for parameter estimation. © 2011, The International Biometric Society.

  20. The Impact of United States Monetary Policy in the Crude Oil futures market

    Science.gov (United States)

    Padilla-Padilla, Fernando M.

    This research examines the empirical impact the United States monetary policy, through the federal fund interest rate, has on the volatility in the crude oil price in the futures market. Prior research has shown how macroeconomic events and variables have impacted different financial markets within short and long--term movements. After testing and decomposing the variables, the two stationary time series were analyzed using a Vector Autoregressive Model (VAR). The empirical evidence shows, with statistical significance, a direct relationship when explaining crude oil prices as function of fed fund rates (t-1) and an indirect relationship when explained as a function of fed fund rates (t-2). These results partially address the literature review lacunas within the topic of the existing implication monetary policy has within the crude oil futures market.

  1. Estimation of transmission mechanism of monetary policy in Serbia

    Directory of Open Access Journals (Sweden)

    Bungin Sanja

    2015-01-01

    Full Text Available Transmission mechanism of monetary policy recently has been subject to several studies in Serbia. The so called 'black box' of monetary policy is investigated with aim to identify the effects of transmission channel in environment where exchange rate has a dominant role in central bank operations. Therefore, it is a challenge to approach this problem in inflation targeting regime where key interest rate is expected to prevail as a main policy instrument. The study employs unrestricted Vector Autoregression model for estimating significance of exchange rate and interest rate channel. As expected, exchange rate has far more stronger influence on inflation, even though there are some signs of interest rate channel existence. Introducing Euribor as endogenous variables in VAR system displayed important impact on real variables.

  2. The Empirical Relationship between Mining Industry Development and Environmental Pollution in China.

    Science.gov (United States)

    Li, Gerui; Lei, Yalin; Ge, Jianping; Wu, Sanmang

    2017-03-02

    This study uses a vector autoregression (VAR) model to analyze changes in pollutants among different mining industries and related policy in China from 2001 to 2014. The results show that: (1) because the pertinence of standards for mining waste water and waste gas emissions are not strong and because the maximum permissible discharge pollutant concentrations in these standards are too high, ammonia nitrogen and industrial sulfur dioxide discharges increased in most mining industries; (2) chemical oxygen demand was taken as an indicator of sewage treatment in environmental protection plans; hence, the chemical oxygen demand discharge decreased in all mining industries; (3) tax reduction policies, which are only implemented in coal mining and washing and extraction of petroleum and natural gas, decreased the industrial solid waste discharge in these two mining industries.

  3. The Empirical Relationship between Mining Industry Development and Environmental Pollution in China

    Directory of Open Access Journals (Sweden)

    Gerui Li

    2017-03-01

    Full Text Available This study uses a vector autoregression (VAR model to analyze changes in pollutants among different mining industries and related policy in China from 2001 to 2014. The results show that: (1 because the pertinence of standards for mining waste water and waste gas emissions are not strong and because the maximum permissible discharge pollutant concentrations in these standards are too high, ammonia nitrogen and industrial sulfur dioxide discharges increased in most mining industries; (2 chemical oxygen demand was taken as an indicator of sewage treatment in environmental protection plans; hence, the chemical oxygen demand discharge decreased in all mining industries; (3 tax reduction policies, which are only implemented in coal mining and washing and extraction of petroleum and natural gas, decreased the industrial solid waste discharge in these two mining industries.

  4. Rediscovery of Impatiens laevigata var. grandifolia (Balsaminaceae from NE India

    Directory of Open Access Journals (Sweden)

    R. Gogoi

    2013-12-01

    Full Text Available Impatiens laevigata var. grandifolia Hook.f. rediscovered after a lapse of 139 years from Lohit district of Arunachal Pradesh. Earlier it was known only – from its type locality in Manipur. Detailed morphological description of I. laevigata var. laevigata and var. grandifolia have been provided based on fresh plant collections.

  5. Genetic analisys of a cross of gaillon (Brassica oleracea var. alboglabra) with cauliflower (B.oleracea var. botrytis)

    OpenAIRE

    Spini, Vanessa B.M.G.; Kerr, Warwick Estevam

    2000-01-01

    The cauliflower (Brassica oleracea var. botrytis) is an annual vegetable cultivated in Southern and Southwestern Brazil with limited production in the Northeast and Centralwest. A variety of Chinese kale, "kaai laan" or "gaillon" (Brassica oleracea var. alboglabra), produces seeds at high temperatures and therefore can do so in North and Northeastern Brazil. Gaillon and cauliflower were crossed 55 times using 10 gaillon plants as mothers and 4 cauliflower plants as pollen donors. From these c...

  6. Order-disorder transitions in time-discrete mean field systems with memory: a novel approach via nonlinear autoregressive models

    International Nuclear Information System (INIS)

    Frank, T D; Mongkolsakulvong, S

    2015-01-01

    In a previous study strongly nonlinear autoregressive (SNAR) models have been introduced as a generalization of the widely-used time-discrete autoregressive models that are known to apply both to Markov and non-Markovian systems. In contrast to conventional autoregressive models, SNAR models depend on process mean values. So far, only linear dependences have been studied. We consider the case in which process mean values can have a nonlinear impact on the processes under consideration. It is shown that such models describe Markov and non-Markovian many-body systems with mean field forces that exhibit a nonlinear impact on single subsystems. We exemplify that such nonlinear dependences can describe order-disorder phase transitions of time-discrete Markovian and non-Markovian many-body systems. The relevant order parameter equations are derived and issues of stability and stationarity are studied. (paper)

  7. Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

    Science.gov (United States)

    Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

    2018-06-01

    Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

  8. Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

    Science.gov (United States)

    Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

    2018-03-01

    Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

  9. Larvicidal Activity of Isodon japonicus var. glaucocalyx (Maxim ...

    African Journals Online (AJOL)

    HP

    Purpose: To determine the larvicidal activity of the essential oil derived from Isodon japonicus var. ... Methods: The essential oil of I. japonicus var. glaucocalyx aerial parts was obtained by ..... µg/mL; G. silvatica leaves, LC50 = 117.9 µg/mL.

  10. Estimating oil price 'Value at Risk' using the historical simulation approach

    International Nuclear Information System (INIS)

    David Cabedo, J.; Moya, Ismael

    2003-01-01

    In this paper we propose using Value at Risk (VaR) for oil price risk quantification. VaR provides an estimation for the maximum oil price change associated with a likelihood level, and can be used for designing risk management strategies. We analyse three VaR calculation methods: the historical simulation standard approach, the historical simulation with ARMA forecasts (HSAF) approach, developed in this paper, and the variance-covariance method based on autoregressive conditional heteroskedasticity models forecasts. The results obtained indicate that HSAF methodology provides a flexible VaR quantification, which fits the continuous oil price movements well and provides an efficient risk quantification

  11. Estimating oil price 'Value at Risk' using the historical simulation approach

    International Nuclear Information System (INIS)

    Cabedo, J.D.; Moya, I.

    2003-01-01

    In this paper we propose using Value at Risk (VaR) for oil price risk quantification. VaR provides an estimation for the maximum oil price change associated with a likelihood level, and can be used for designing risk management strategies. We analyse three VaR calculation methods: the historical simulation standard approach, the historical simulation with ARMA forecasts (HSAF) approach. developed in this paper, and the variance-covariance method based on autoregressive conditional heteroskedasticity models forecasts. The results obtained indicate that HSAF methodology provides a flexible VaR quantification, which fits the continuous oil price movements well and provides an efficient risk quantification. (author)

  12. ClinVar data parsing [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Xiaolei Zhang

    2017-05-01

    Full Text Available This software repository provides a pipeline for converting raw ClinVar data files into analysis-friendly tab-delimited tables, and also provides these tables for the most recent ClinVar release. Separate tables are generated for genome builds GRCh37 and GRCh38 as well as for mono-allelic variants and complex multi-allelic variants. Additionally, the tables are augmented with allele frequencies from the ExAC and gnomAD datasets as these are often consulted when analyzing ClinVar variants. Overall, this work provides ClinVar data in a format that is easier to work with and can be directly loaded into a variety of popular analysis tools such as R, python pandas, and SQL databases.

  13. Pitfalls in VAR based return decompositions: A clarification

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard; Tanggaard, Carsten

    in their analysis is not "cashflow news" but "inter- est rate news" which should not be zero. Consequently, in contrast to what Chen and Zhao claim, their decomposition does not serve as a valid caution against VAR based decompositions. Second, we point out that in order for VAR based decompositions to be valid......Based on Chen and Zhao's (2009) criticism of VAR based return de- compositions, we explain in detail the various limitations and pitfalls involved in such decompositions. First, we show that Chen and Zhao's interpretation of their excess bond return decomposition is wrong: the residual component...

  14. Medium- and Long-term Prediction of LOD Change with the Leap-step Autoregressive Model

    Science.gov (United States)

    Liu, Q. B.; Wang, Q. J.; Lei, M. F.

    2015-09-01

    It is known that the accuracies of medium- and long-term prediction of changes of length of day (LOD) based on the combined least-square and autoregressive (LS+AR) decrease gradually. The leap-step autoregressive (LSAR) model is more accurate and stable in medium- and long-term prediction, therefore it is used to forecast the LOD changes in this work. Then the LOD series from EOP 08 C04 provided by IERS (International Earth Rotation and Reference Systems Service) is used to compare the effectiveness of the LSAR and traditional AR methods. The predicted series resulted from the two models show that the prediction accuracy with the LSAR model is better than that from AR model in medium- and long-term prediction.

  15. What is Orobanche haenseleri var. deludens Beck?

    Directory of Open Access Journals (Sweden)

    Pujadas Salvà, Antonio J.

    2004-12-01

    Full Text Available Orobanche haenseleri var. deludens Beck (Orobanchaceae, a problematic taxon described from Algeciras (Cádiz, S Spain is here identified after studying the original material of Wolley-Dod (BM 4476. It is considered to be the same as O. austrohispanica M.J.Y. Foley and better included, as a variety, under O. gracilis Sm. The new combination O. gracilis var. deludens (Beck A. Pujadas is consequently proposed. It mainly parasites Ulex (Fabaceae in the western Mediterranean Region (Iberian Peninsula and NW Africa.Se identifica Orobanche haenseleri var. deludens Beck (Orobanchaceae, un taxon conflictivo descrito de Algeciras (Cádiz, sur de España, a partir del análisis del material original de Wolley-Dod (BM 4476. Se considera que es lo mismo que O. austrohispanica M.J.Y. Foley, y se incluye en O. gracilis Sm. con rango varietal. Se propone la nueva combinación O. gracilis var. deludens (Beck A. Pujadas. Parasita principalmente a especies del género Ulex (Fabaceae en la Región Mediterránea Occidental (Península Ibérica y noroeste de África.

  16. Growth and provenance variation of Pinus caribaea var ...

    African Journals Online (AJOL)

    CAMCORE has visited 33 populations of Pinus caribaea var. hondurensis in Belize, Guatemala, Honduras, El Salvador, Nicaragua, and Quintana Roo, Mexico. Seed collections have been made in 29 provenances from 1, 325 mother trees. A total of 21 provenances and sources of Pinus caribaea var. hondurensis were ...

  17. On the Oracle Property of the Adaptive LASSO in Stationary and Nonstationary Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    We show that the Adaptive LASSO is oracle efficient in stationary and non-stationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...

  18. A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution.

    Science.gov (United States)

    Lee, Duncan; Rushworth, Alastair; Sahu, Sujit K

    2014-06-01

    Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models. © 2014, The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  19. Aviation Trainer Technology Test Plan. Volume II. Software Development

    Science.gov (United States)

    1991-11-25

    feild values in new node *Ieg>X=x newg->X = Y newg->Len =len; newg->Help =help; newg->Ignore = ignore; newg->Format = format; newg->Validation - NULL;I... vector : North long varVFE; /* F-16A velocity vector : East long varVFU; /* F-16A velocity vector : Up */ long varH; /* plane heading */ long varC; /* plane...31\\\\ETH523.sys" parmsdr.args=getds(); parmsdr.non7=OxOO; /*save interrupt vector for future restoration */ cSavvecso; rc=getdso; rc=cInitParameters

  20. Empirical analysis on future-cash arbitrage risk with portfolio VaR

    Science.gov (United States)

    Chen, Rongda; Li, Cong; Wang, Weijin; Wang, Ze

    2014-03-01

    This paper constructs the positive arbitrage position by alternating the spot index with Chinese Exchange Traded Fund (ETF) portfolio and estimating the arbitrage-free interval of futures with the latest trade data. Then, an improved Delta-normal method was used, which replaces the simple linear correlation coefficient with tail dependence correlation coefficient, to measure VaR (Value-at-risk) of the arbitrage position. Analysis of VaR implies that the risk of future-cash arbitrage is less than that of investing completely in either futures or spot market. Then according to the compositional VaR and the marginal VaR, we should increase the futures position and decrease the spot position appropriately to minimize the VaR, which can minimize risk subject to certain revenues.

  1. Quercetin - A Flavonoid Compound from Sarcopyramis bodinieri var ...

    African Journals Online (AJOL)

    DAPI staining and PARP SDS-PAGE tests showed 60 μM quercetin could induce potential apoptotic activity in HepG2 liver cancer cells. Conclusion: Quercetin was the major cytotoxicity constituent in S. bodinieri var. delicate. Keywords: Apoptotic activity, Quercetin, Sarcopyramis bodinieri var. delicate, HepG2 liver cancer ...

  2. Identification of the relationship between Chinese Adiantum reniforme var. sinense and Canary Adiantum reniforme.

    Science.gov (United States)

    Wang, Ai-Hua; Sun, Ye; Schneider, Harald; Zhai, Jun-Wen; Liu, Dong-Ming; Zhou, Jin-Song; Xing, Fu-Wu; Chen, Hong-Feng; Wang, Fa-Guo

    2015-02-05

    There are different opinions about the relationship of two disjunctively distributed varieties Adiantum reniforme L. var. sinense Y.X.Lin and Adiantum reniforme L. Adiantum reniforme var. sinense is an endangered fern only distributed in a narrowed region of Chongqing city in China, while Adiantum reniforme var. reniforme just distributed in Canary Islands and Madeira off the north-western African coast. To verify the relationship of these two taxa, relative phylogenetic analyses, karyotype analyses, microscopic spore observations and morphological studies were performed in this study. Besides, divergence time between A. reniforme var. sinense and A. reniforme var. reniforme was estimated using GTR model according to a phylogeny tree constructed with the three cpDNA markers atpA, atpB, and rbcL. Phylogenetic results and divergence time analyses--all individuals of A. reniforme var. sinense from 4 different populations (representing all biogeographic distributions) were clustered into one clade and all individuals of A. reniforme var. reniforme from 7 different populations (all biogeographic distributions are included) were clustered into another clade. The divergence between A. reniforme var. reniforme and A. reniforme var. sinense was estimated to be 4.94 (2.26-8.66) Myr. Based on karyotype analyses, A. reniforme var. reniforme was deduced to be hexaploidy with 2n = 180, X = 30, while A. reniforme var. sinense was known as tetraploidy. Microscopic spore observations suggested that surface ornamentation of A. reniforme var. reniforme is psilate, but that of A. reniforme var. sinense is rugate. Leaf blades of A. reniforme var. sinense are membranous and reniform and with several obvious concentric rings, and leaves of A. reniforme var. reniforme are pachyphyllous and coriaceous and are much rounder and similar to palm. Adiantum reniforme var. sinense is an independent species rather than the variety of Adiantum reniforme var. reniforme. As a result, we

  3. Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

    Science.gov (United States)

    Nabelek, Daniel P.; Ho, K. C.

    2013-06-01

    The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an Ascan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m2.

  4. Energy conservation and sustainable economic growth: The case of Latin America and the Caribbean

    International Nuclear Information System (INIS)

    Chang, Ching-Chih; Soruco Carballo, Claudia Fabiola

    2011-01-01

    This study examines the causal relationships among energy consumption, economic growth and carbon dioxide emissions in twenty countries from Latin America and the Caribbean region. The methodology includes the use of Phillips and Perron (PP) tests, a cointegration model with vector error correction modeling (VECM) and vector autoregression (VAR) with Granger causality. The study concludes that of the twenty countries analyzed, only in four of them will it be possible to implement energy conservation polices without affecting their economic growth, four others are not able to consider an energy conservation policy with economic growth, and the other twelve should focus on their economic growth before adopting any conservation policies. Energy efficiency was found in this region, especially in the countries which have both cointegration and short-term equilibrium. - Highlights: → Only four countries could implement energy conservation polices without affecting economic growth. → Twelve nations should focus on their economic growth before designing any energy conservation policies. → Energy efficiency was found in the countries which have both cointegration and short-term equilibrium.

  5. Obtaining of transgenic papaya plants var. Maradol roja that carry out the rice oryzacystatin gene

    Directory of Open Access Journals (Sweden)

    Milady F. Mendoza

    2004-10-01

    Full Text Available Papaya (Carica papaya L., is severely affected by Papaya Ringspot virus, which belongs to plant potyvirus group. A recent strategy for pest control produced by this virus is the transformation with genes encoding cysteine proteinase inhibitors. Rice oryzacistatin gene encoding for cystatins, was inserted in a pCAMBIA binary vector, for genetic transformation of papaya somatic embryos var. Maradol roja, mediated by gene gun. Gene integration was confirmed by means of polimerase chain reaction using the primers designed from gene bar sequence. Forty out of eighty in vitro transgenic papaya lines amplified a 402 fragment which correspond to the expecting size. Key words: Carica papaya, genetic engineering, potyvirus, proteinase inhibitor

  6. Search for pair-produced vector-like quarks with the ATLAS detector

    CERN Document Server

    Succurro, A

    2013-01-01

    The high energy frontier opened by the LHC is allowing us to explore physics scenarios where new physics might lay. The need to go beyond the Standard Model (SM) comes from var\\ ious unanswered questions, like where does the matter-antimatter asymmetry comes from? What is the nature of Dark Matter? How can the hierarchy problem be solved? The recent di\\ scovery of an Higgs-like boson tends to disfavour the existence of a heavy 4th generation of quarks which would change the Higgs SM cross section and branching ratio in a way i\\ t is not experimentally observed. At the same time, vector-like quarks become a more compelling possibility due to their important role stabilizing the Higgs boson mass against\\ radiative corrections. The purpose of this poster is to review the latest results in the searches for pair production of vector-like quarks at the ATLAS experiment.

  7. Foco de leishmaniasis en El Hobo, municipio de El Carmen de Bolívar, Bolívar, Colombia

    Directory of Open Access Journals (Sweden)

    Luis Alberto Cortés

    2006-10-01

    Full Text Available Introducción. Se describen las características epidemiológica e importancia de la especies de Lutzomyia presentes en un foco de leishmaniasis en la vereda El Hobo Carmen de Bolívar, departamento de Bolívar. Objetivos. Obtener un conocimiento preliminar de la transmisión de leishmaniasis en la vereda El Hobo Carmen de Bolívar. Materiales y métodos. Se analizaron datos epidemiológicos y se realizaron capturas de flebótomos con trampas CDC y cebo humano en la vereda El Hobo. Para establecer la sero prevalencia de leishmaniasis visceral canina se hizo un estudio en perros mediante la técnica de inmunofluorescencia indirecta. Resultados. Se capturaron nueve especies de Lutzomyia: L. trinidadensis, L. evansi, L .cayennensis, L. venezuelensis, L. gomezi,L. dubitans, L. ylephiletor, L. yuilli, y L. walkeri. Las especie de mayor importancia por sus implicaciones en la transmisión de leishmaniasis cutánea y visceral fueron L. gomezi, y L. evansi respectivamente. Se reporta por primera vez para Bolívar especimenes de L. venezuelensis, L. dubitans, L. ylephiletor, L. yuilli, y L. walkeri. Se determinó una prevalencia de leishmaniasis visceral del 36% en los caninos estudiados. Según los reportes epidemiológicos, en el 2002 en el municipio de Carmen de Bolívar la leishmaniasis cutánea mostró un aumento del 40% y la leishmaniasis visceral canina del 80% de los casos con respecto al 2001, debido al brote presentado en la vereda El Hobo Conclusiones. Los resultados determinan a la vereda El Hobo como una zona de riesgo potencial de transmisión de leishmaniasis cutánea y visceral.

  8. Phosphorylation of SU(VAR3-9 by the chromosomal kinase JIL-1.

    Directory of Open Access Journals (Sweden)

    Joern Boeke

    2010-04-01

    Full Text Available The histone methyltransferase SU(VAR3-9 plays an important role in the formation of heterochromatin within the eukaryotic nucleus. Several studies have shown that the formation of condensed chromatin is highly regulated during development, suggesting that SU(VAR3-9's activity is regulated as well. However, no mechanism by which this may be achieved has been reported so far. As we and others had shown previously that the N-terminus of SU(VAR3-9 plays an important role for its activity, we purified interaction partners from Drosophila embryo nuclear extract using as bait a GST fusion protein containing the SU(VAR3-9 N-terminus. Among several other proteins known to bind Su(VAR3-9 we isolated the chromosomal kinase JIL-1 as a strong interactor. We show that SU(VAR3-9 is a substrate for JIL-1 in vitro as well as in vivo and map the site of phosphorylation. These findings may provide a molecular explanation for the observed genetic interaction between SU(VAR3-9 and JIL-1.

  9. Time series analysis of wind speed using VAR and the generalized impulse response technique

    Energy Technology Data Exchange (ETDEWEB)

    Ewing, Bradley T. [Area of Information Systems and Quantitative Sciences, Rawls College of Business and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX 79409-2101 (United States); Kruse, Jamie Brown [Center for Natural Hazard Research, East Carolina University, Greenville, NC (United States); Schroeder, John L. [Department of Geosciences and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States); Smith, Douglas A. [Department of Civil Engineering and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States)

    2007-03-15

    This research examines the interdependence in time series wind speed data measured in the same location at four different heights. A multiple-equation system known as a vector autoregression is proposed for characterizing the time series dynamics of wind. Additionally, the recently developed method of generalized impulse response analysis provides insight into the cross-effects of the wind series and their responses to shocks. Findings are based on analysis of contemporaneous wind speed time histories taken at 13, 33, 70 and 160 ft above ground level with a sampling rate of 10 Hz. The results indicate that wind speeds measured at 70 ft was the most variable. Further, the turbulence persisted longer at the 70-ft measurement than at the other heights. The greatest interdependence is observed at 13 ft. Gusts at 160 ft led to the greatest persistence to an 'own' shock and led to greatest persistence in the responses of the other wind series. (author)

  10. Fitting multistate transition models with autoregressive logistic regression : Supervised exercise in intermittent claudication

    NARCIS (Netherlands)

    de Vries, S O; Fidler, Vaclav; Kuipers, Wietze D; Hunink, Maria G M

    1998-01-01

    The purpose of this study was to develop a model that predicts the outcome of supervised exercise for intermittent claudication. The authors present an example of the use of autoregressive logistic regression for modeling observed longitudinal data. Data were collected from 329 participants in a

  11. 21 CFR 173.145 - Alpha-Galactosidase derived from Mortierella vinaceae var. raffinoseutilizer.

    Science.gov (United States)

    2010-04-01

    ... vinaceae var. raffinoseutilizer. 173.145 Section 173.145 Food and Drugs FOOD AND DRUG ADMINISTRATION... Alpha-Galactosidase derived from Mortierella vinaceae var. raffinoseutilizer. The food additive alpha-galactosidase and parent mycelial microorganism Mortierella vinaceae var. raffinoseutilizer may be safely used...

  12. Comparative ozone responses of cutleaf coneflowers (Rudbeckia laciniata var. digitata, var. ampla) from Rocky Mountain and Great Smoky Mountains National Parks, USA.

    Science.gov (United States)

    Neufeld, Howard S; Johnson, Jennifer; Kohut, Robert

    2018-01-01

    Cutleaf coneflower (Rudbeckia laciniata L. var. digitata) is native to Great Smoky Mountains National Park (GRSM) and an ozone bioindicator species. Variety ampla, whose ozone sensitivity is less well known, is native to Rocky Mountain National Park (ROMO). In the early 2000s, researchers found putative ozone symptoms on var. ampla and rhizomes were sent to Appalachian State University to verify that the symptoms were the result of ozone exposure. In 2011, potted plants were exposed to ambient ozone from May to August. These same plants were grown in open-top chambers (OTCs) in 2012 and 2013, and exposed to charcoal-filtered (CF), non-filtered (NF), elevated ozone (EO), NF+50ppb in 2012 for 47days and NF+30/NF+50ppb ozone in 2013 for 36 and 36days, respectively. Ozone symptoms similar to those found in ROMO (blue-black adaxial stippling) were reproduced both in ambient air and in the OTCs. Both varieties exhibited foliar injury in the OTCs in an exposure-dependent manner, verifying that symptoms resulted from ozone exposure. In two of the three study years, var. digitata appeared more sensitive than var. ampla. Exposure to EO caused reductions in ambient photosynthetic rate (A) and stomatal conductance (g s ) for both varieties. Light response curves indicated that ozone reduced A, g s , and the apparent quantum yield while it increased the light compensation point. In CF air, var. ampla had higher light saturated A (18.2±1.04 vs 11.6±0.37μmolm -2 s -1 ), higher light saturation (1833±166.7 vs 1108±141.7μmolm -2 s -1 ), and lower Ci/Ca ratio (0.67±0.01 vs 0.77±0.01) than var. digitata. Coneflowers in both Parks are adversely affected by exposure to ambient ozone and if ozone concentrations increase in the Rocky Mountains, greater amounts of injury on var. ampla can be expected. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. VAr reserve concept applied to a wind power plant

    DEFF Research Database (Denmark)

    Martinez, Jorge; Kjær, Philip C.; Rodriguez, Pedro

    2011-01-01

    to wind power plants. This paper proposes two different VAr reserve control strategies for a wind power plant. The amount of dynamic VAr available most of the operation time, makes the wind power plant (WPP) a good candidate to include a VAr reserve management system. Two different ways of implementing...... a VAr management system are proposed and analyzed. Such a reactive power reserve may be provided by the wind power plant since the amount of reactive power installed for most active power working points exceeds the demand required by the grid operator. Basically, this overrated reactive power capacity...... is a consequence of sizing wind turbine facilities for maximum active power level. The reactive power losses, due to active power transportation inside the plant (normally two transformers), and P-Q wind turbine characteristics define the P-Q reserve chart. By utilizing the intrinsic overrated reactive power...

  14. A comprehensive market-based scheme for VAR management and pricing in the electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    El-Araby, E.E. [Qassim Univ., Alqassim, Meldia (Saudi Arabia). Dept. of Electrical Engineering

    2009-07-01

    In order to enable a power system to operate within an acceptable degree of reliability and security, the provision of VAR ancillary services from the VAR sources in electricity markets is the most effective method. The procurement of VAR services is particularly problematic for transmission operators as it relates to pricing mechanism and various technical issues during system operation. This paper proposed an integrated market-based approach for pricing VAR service in the electricity market. The paper was an extension of the authors' proposal for the provision of the VAR service from dynamic VAR sources in a competitive market-based environment. The formulation was modified to include VAR utilization payment and possible power system transition states multiple base cases and contingencies with their associated occurrence probabilities. The paper discussed the basic terms of the proposed approach including the VAR market objective and generator VAR output and its compensation. The mathematical formulation that considered VAR capacity payment, utilization payment and operating costs under the previous transition states in a unified single problem were introduced. The overall problem formulation and solution algorithm were also presented as a large-scale mixed integer nonlinear optimization problem. It was concluded that the proposed method was suited for the simulation and analysis of the existing VAR market. 8 refs., 3 tabs., 5 figs., 2 appendices.

  15. Bias-corrected estimation in potentially mildly explosive autoregressive models

    DEFF Research Database (Denmark)

    Haufmann, Hendrik; Kruse, Robinson

    This paper provides a comprehensive Monte Carlo comparison of different finite-sample bias-correction methods for autoregressive processes. We consider classic situations where the process is either stationary or exhibits a unit root. Importantly, the case of mildly explosive behaviour is studied...... that the indirect inference approach oers a valuable alternative to other existing techniques. Its performance (measured by its bias and root mean squared error) is balanced and highly competitive across many different settings. A clear advantage is its applicability for mildly explosive processes. In an empirical...

  16. To the issue of increasing efficiency of VAR compensation

    Directory of Open Access Journals (Sweden)

    Світлана Костянтинівна Поднебенна

    2015-11-01

    Full Text Available This article describes the features of VAR compensation of variable loads. One of the most common non-symmetric non-linear power consumers are welding power sources. Time and duration of the work of these sources vary randomly. To compensate the consumption of reactive power on the basis of consumption data from the three-phase electricity meters is inefficient. Compensation devices power should be calculated taking into account the asymmetrical consumption/generation of reactive power per phase and changing consumption patterns. Thyristor-controlled reactor, thyristor-switched capacitors, hybrid VAR compensators, active compensators (STATCOMs, «dynamic capacitors» can be used as the VAR compensation devices. Thyristor-controlled reactors can provide smooth regulation of reactive power, but they have high weight and size parameters and are additional sources of higher harmonics. Thyristor-switched capacitors provide stepwise adjustment of reactive power and are subject to the current higher harmonics. Hybrid VAR compensators make it possible to isolate capacitors from the higher harmonics and ensure smooth regulation, which is achieved by active filter introduction to the reactive power compensation devices based on thyristor-switched capacitors. However, this increases the cost of a compensator and complicates its control system. STATCOMs provide smooth regulation of reactive power, but they are too expensive.Perspective direction in the development of effective VAR compensation devices is «dynamic capacitor». As a result of a feasibility study the prospects for further research of electrical grids power efficiency through the development of effective devices for VAR compensation have been established

  17. On the Stationarity of Multiple Autoregressive Approximants: Theory and Algorithms

    Science.gov (United States)

    1976-08-01

    a I (3.4) Hannan and Terrell (1972) consider problems of a similar nature. Efficient estimates A(1),... , A(p) , and i of A(1)... ,A(p) and...34Autoregressive model fitting for control, Ann . Inst. Statist. Math., 23, 163-180. Hannan, E. J. (1970), Multiple Time Series, New York, John Wiley...Hannan, E. J. and Terrell , R. D. (1972), "Time series regression with linear constraints, " International Economic Review, 13, 189-200. Masani, P

  18. Exchange Rates’ Effect on Spot and Futures Equity Index Markets: A Study on Borsa Istanbul

    Directory of Open Access Journals (Sweden)

    Ayben Koy

    2017-06-01

    Full Text Available This paper examines the linkages between the foreign exchange rates, spot equity index and equity index futures. The study aims to investi-gate whether there is difference between the spot and futures markets in the scope of relation with the foreign exchange rates’ returns and which leads the other. The relationships are examined by using the vector autoregression (VAR model, impulse-response functions, variance decomposition and Granger Causality tests. The sample of the study consists of US dollar to Turkish Lira rate (USD/TRY, Euro to Turkish Lira rate (EUR/TRY, BIST 30 Index and BIST 30 Index Futures. The data of the study includes the period between January 2011 and December 2014 with daily data range. Our results have evidence that the foreign exchange rate markets in Turkey are driven by the equity market.

  19. How can the origin of the decay var-phi →3π be determined?

    International Nuclear Information System (INIS)

    Achasov, N.N.; Kozhevnikov, A.A.

    1992-01-01

    It is shown that the interference pattern in the region √s = 1.05 GeV in the reaction e + e - →ω, var-phi →3π can be used to determine unambiguously whether the decay var-phi →3π occurs because of var-phi ω mixing, var-phi →ω→3π, or because of the direct transition var-phi →3π. 8 refs., 3 figs., 1 tab

  20. Consistent and Conservative Model Selection with the Adaptive LASSO in Stationary and Nonstationary Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    2016-01-01

    We show that the adaptive Lasso is oracle efficient in stationary and nonstationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...

  1. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, R.N.J.; Vries, L.B.

    1986-01-01

    The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  2. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, Raymond N.J.; Vries, Lodewijk B.

    1986-01-01

    This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  3. Recursive wind speed forecasting based on Hammerstein Auto-Regressive model

    International Nuclear Information System (INIS)

    Ait Maatallah, Othman; Achuthan, Ajit; Janoyan, Kerop; Marzocca, Pier

    2015-01-01

    Highlights: • Developed a new recursive WSF model for 1–24 h horizon based on Hammerstein model. • Nonlinear HAR model successfully captured chaotic dynamics of wind speed time series. • Recursive WSF intrinsic error accumulation corrected by applying rotation. • Model verified for real wind speed data from two sites with different characteristics. • HAR model outperformed both ARIMA and ANN models in terms of accuracy of prediction. - Abstract: A new Wind Speed Forecasting (WSF) model, suitable for a short term 1–24 h forecast horizon, is developed by adapting Hammerstein model to an Autoregressive approach. The model is applied to real data collected for a period of three years (2004–2006) from two different sites. The performance of HAR model is evaluated by comparing its prediction with the classical Autoregressive Integrated Moving Average (ARIMA) model and a multi-layer perceptron Artificial Neural Network (ANN). Results show that the HAR model outperforms both the ARIMA model and ANN model in terms of root mean square error (RMSE), mean absolute error (MAE), and Mean Absolute Percentage Error (MAPE). When compared to the conventional models, the new HAR model can better capture various wind speed characteristics, including asymmetric (non-gaussian) wind speed distribution, non-stationary time series profile, and the chaotic dynamics. The new model is beneficial for various applications in the renewable energy area, particularly for power scheduling

  4. Forecasting Construction Tender Price Index in Ghana using Autoregressive Integrated Moving Average with Exogenous Variables Model

    Directory of Open Access Journals (Sweden)

    Ernest Kissi

    2018-03-01

    Full Text Available Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.

  5. How Does the Financial Crisis Affect Volatility Behavior and Transmission Among European Stock Markets?

    Directory of Open Access Journals (Sweden)

    Faten Ben Slimane

    2013-08-01

    Full Text Available The spread of the global financial crisis of 2008/2009 was rapid, and impacted the functioning and the performance of financial markets. Due to the importance of this phenomenon, this study aims to explain the impact of the crisis on stock market behavior and interdependence through the study of the intraday volatility transmission. This paper investigates the patterns of linkage dynamics among three European stock markets—France, Germany, and the UK—during the global financial crisis, by analyzing the intraday dynamics of linkages among these markets during both calm and turmoil phases. We apply a VAR-EGARCH (Vector Autoregressive Exponential General Autoregressive Conditional Heteroscedasticity framework to high frequency five-minute intraday returns on selected representative stock indices. We find evidence that interrelationship among European markets increased substantially during the period of crisis, pointing to an amplification of spillovers. In addition, during this period, French and UK markets herded around German market, possibly explained by behavior factors influencing the stock markets on or near dates of extreme events. Germany was identified as the hub of financial and economic activity in Europe during the period of study. These findings have important implications for both policymakers and investors by contributing to better understanding the transmission of financial shocks in Europe.

  6. VAR, stress-testing and supplementary methodologies: uses and constraints in energy risk management

    International Nuclear Information System (INIS)

    Senior, Brian

    1999-01-01

    This chapter lists some of the special risks associated with a range of energy markets, and questions what is risk. Market risk, the use of value-at-risk (VAR) for measuring and managing market risk, use of VAR in the banking sector, back-testing of VAR, the corporate sector, making investment decisions, and the need for additional methods of risk analysis are discussed. Scenario analysis and stress testing, liquidity, and combining VAR and stress-testing are described. Credit risk and the quantitative analysis of credit risk are addressed, and operational risk, and organisational challenges are considered. Panels present examples of a simple VAR calculation and give descriptions of VAR in corporate decisions, the measurement of liquidity, and the use of the Greeks in decisions on day to day trading and risk management

  7. EFEITO FUNGITÓXICO DO ÓLEO DE NIM SOBRE Metarhizium anisopliae var. acridum e Metarhizium anisopliae var. anisopliae

    Directory of Open Access Journals (Sweden)

    Álison Bruno da Silva Santos

    2009-01-01

    Full Text Available Plague control is based almost exclusively on application of chemical substances, however these products are toxic to men and animals and cause odd effects on environment quality. In Plague Integrated Management (PIM, the use of selected insecticides and entomopathogenic fungi should be considered as one viable strategy for plague control in agriculture. This work aimed to evaluate, in laboratory, the compatibility of the entomopathogenic fungi Metarhizium anisopliae var. acridum and Metarhizium anisopliae var. anisopliae with the oil of Nim. The addition of the product was made to the potato-dextrose-agar medium still liquid (±45°C, in a way that the final concentration obeyed 50% of the producer's recommendation. After fungi inoculation, the dishes were incubated in a cimatized room at 28°C, photophase of 12 hours and relative humidity of 75±5% for 12 day period. The number of conidia per colonie was counted with a Neubauer chamber. Statistic delineament was entirely in random, with two treatments (PDA with insecticide, and a control group (PDA without insecticide, and 9 repetitions for each treatment. The results showed that the insecticide inhibited conidial production in Metarhizium anisopliae var. anisopliae strains when compared to the control group. The diameter of Metarhizium anisopliae var. acridum colonies suffered significative reduction in its size, compared to control. The tested insecticide, in the concentration and formulation used, presented compatibility with the tested strains.

  8. Saccharomyces cerevisiae var. boulardii fungemia following probiotic treatment

    OpenAIRE

    Appel-da-Silva, Marcelo C.; Narvaez, Gabriel A.; Perez, Leandro R.R.; Drehmer, Laura; Lewgoy, Jairo

    2017-01-01

    Probiotics are commonly prescribed as an adjuvant in the treatment of antibiotic-associated diarrhea caused by Clostridium difficile. We report the case of an immunocompromised 73-year-old patient on chemotherapy who developed Saccharomyces cerevisiae var. boulardii fungemia in a central venous catheter during treatment of antibiotic-associated pseudomembranous colitis with the probiotic Saccharomyces cerevisiae var. boulardii. Fungemia was resolved after interruption of probiotic administrat...

  9. An Application of Non-Linear Autoregressive Neural Networks to Predict Energy Consumption in Public Buildings

    Directory of Open Access Journals (Sweden)

    Luis Gonzaga Baca Ruiz

    2016-08-01

    Full Text Available This paper addresses the problem of energy consumption prediction using neural networks over a set of public buildings. Since energy consumption in the public sector comprises a substantial share of overall consumption, the prediction of such consumption represents a decisive issue in the achievement of energy savings. In our experiments, we use the data provided by an energy consumption monitoring system in a compound of faculties and research centers at the University of Granada, and provide a methodology to predict future energy consumption using nonlinear autoregressive (NAR and the nonlinear autoregressive neural network with exogenous inputs (NARX, respectively. Results reveal that NAR and NARX neural networks are both suitable for performing energy consumption prediction, but also that exogenous data may help to improve the accuracy of predictions.

  10. Genomic resources and draft assemblies of the human and porcine varieties of scabies mites, Sarcoptes scabiei var. hominis and var. suis.

    Science.gov (United States)

    Mofiz, Ehtesham; Holt, Deborah C; Seemann, Torsten; Currie, Bart J; Fischer, Katja; Papenfuss, Anthony T

    2016-06-02

    The scabies mite, Sarcoptes scabiei, is a parasitic arachnid and cause of the infectious skin disease scabies in humans and mange in other animal species. Scabies infections are a major health problem, particularly in remote Indigenous communities in Australia, where secondary group A streptococcal and Staphylococcus aureus infections of scabies sores are thought to drive the high rate of rheumatic heart disease and chronic kidney disease. We sequenced the genome of two samples of Sarcoptes scabiei var. hominis obtained from unrelated patients with crusted scabies located in different parts of northern Australia using the Illumina HiSeq. We also sequenced samples of Sarcoptes scabiei var. suis from a pig model. Because of the small size of the scabies mite, these data are derived from pools of thousands of mites and are metagenomic, including host and microbiome DNA. We performed cleaning and de novo assembly and present Sarcoptes scabiei var. hominis and var. suis draft reference genomes. We have constructed a preliminary annotation of this reference comprising 13,226 putative coding sequences based on sequence similarity to known proteins. We have developed extensive genomic resources for the scabies mite, including reference genomes and a preliminary annotation.

  11. Assessment of surface runoff depth changes in S\\varǎţel River basin, Romania using GIS techniques

    Science.gov (United States)

    Romulus, Costache; Iulia, Fontanine; Ema, Corodescu

    2014-09-01

    S\\varǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in S\\varǎţel catchment, between 1990-2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.

  12. [Autotoxicity of aqueous extracts from plant of cultivated Astragalus membranaceus var. mongholicus].

    Science.gov (United States)

    Zhang, Xin-Hui; Lang, Duo-Yong; Chen, Jing; Zhao, Yun-Sheng; Wu, Xiu-Li; Fu, Xue-Yan

    2014-02-01

    To exploring the relationship between continuous cropping obstacle and autotoxicity of Astragalus membranaceus var. mongholicus, autotoxic effect of plant aqueous extract were determined. Distilled water (CK), aqueous extract of plant, including root, stem and leaf (12.5, 25, 50 and 100 mg/mL respectively)were applied to testing their effect on early growth of Astragalus membranaceus var. mongholicus. Specifically, seed germination rate, germination index, emergence rate, elongation of radical and embryo, and seedling vigor index were determined. The aqueous extract of root, stem, and leaf at 25 mg/mL significantly inhibited the seed germination and seedling growth of Astragalus membranaceus var. mongholicus, and this inhibitory effect generally increased with the increase of the concentration of aqueous extracts. To the comprehensive allelopathic effect, the extracts from Astragalus membranaceus var. mongholicus stem were more inhibitory than those from leaf and root. The germination index and seedling vigor index were more sensitive to extract than other determined parameters. Aqueous extracts from Astragalus membranaceus var. mongholicus plant gave inhibitory effects on Astragalus. membranaceus var. mongholicus germination and seedling growth, and this inhibitory effect generally increased with the increases of aqueous extract concentration at a certain ranges. In conclusion, there is an autotoxicity in continuous cropping of Astragalus membranaceus var. mongholicus.

  13. [Photosynthetic parameters and physiological indexes of Paris polyphylla var. yunnanensis influenced by arbuscular mycorrhizal fungi].

    Science.gov (United States)

    Wei, Zheng-xin; Guo, Dong-qin; Li, Hai-feng; Ding, Bo; Zhang, Jie; Zhou, Nong; Yu, Jie

    2015-10-01

    Through potted inoculation test at room temperature and indoor analysis, the photosynthetic parameters and physiological and biochemical indexes of Paris polyphylla var. yunnanensis were observed after 28 arbuscular mycorrhizal (AM) fungi were injected into the P. polyphylla var. yunnanensis growing in a sterile soil environment. The results showed that AM fungi established a good symbiosis with P. polyphylla var. yunnanensis. The AM fungi influenced the photosynthetic parameters and physiological and biochemical indexes of P. polyphylla var. yunnanensis. And the influences were varied depending on different AM fungi. The application of AM fungi improved photosynthesis intensity of P. polyphylla var. yunnanensis mesophyll cells, the contents of soluble protein and soluble sugar, protective enzyme activity of P. polyphylla var. yunnanensis leaf, which was beneficial to resist the adverse environment and promote the growth of P. polyphylla var. yunnanensis. Otherwise, there was a certain mutual selectivity between P. polyphylla var. yunnanensis and AM fungi. From the comprehensive effect of inoculation, Racocetra coralloidea, Scutellospora calospora, Claroideoglomus claroideum, S. pellucida and Rhizophagus clarus were the most suitable AM fungi to P. polyphylla var. yunnanensis when P. polyphylla var. yunnanensis was planted in the field.

  14. Testing Fiscal Dominance Hypothesis in a Structural VAR Specification for Pakistan

    Directory of Open Access Journals (Sweden)

    Shaheen Rozina

    2018-03-01

    Full Text Available This research aims to test the fiscal dominance hypothesis for Pakistan through a bivariate structural vector auto regression (SVAR specification, covering time period 1977 – 2016. This study employs real primary deficit (non interest government expenditures minus total revenues and real primary liabilities (sum of monetary base and domestic public debt as indicators of fiscal measures and monetary policy respectively. A structural VAR is retrieved both for entire sample period and four sub periods (1977 – 1986, 1987 – 1997, 1998 – 2008, and 2009 – 2016. This study identifies the presence of fiscal dominance for the entire sample period and the sub period from 1987 – 2008. The estimates reveal an interesting phenomenon that fiscal dominance is significant in the elected regimes and weaker in the presence of military regimes in Pakistan. From a policy perspective, this research suggests increased autonomy of central bank to achieve long term price stability and reduced administration costs to ensure efficient democratic regime in Pakistan.

  15. Autoregressive Model with Partial Forgetting within Rao-Blackwellized Particle Filter

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil; Hofman, Radek

    2012-01-01

    Roč. 41, č. 5 (2012), s. 582-589 ISSN 0361-0918 R&D Projects: GA MV VG20102013018; GA ČR GA102/08/0567 Grant - others:ČVUT(CZ) SGS 10/099/OHK3/1T/16 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian methods * Particle filters * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.295, year: 2012 http://library.utia.cas.cz/separaty/2012/AS/dedecius-autoregressive model with partial forgetting within rao-blackwellized particle filter.pdf

  16. Impulse-response analysis of monetary policy – Visegád group countries case

    Directory of Open Access Journals (Sweden)

    Kateřina Myšková

    2013-01-01

    Full Text Available In this paper, we focus on comparability of monetary policies of Visegrád group countries (V4. Main objective of central banks function in V4 countries lies in maintaining price stability. For this purpose, inflation targeting regime is realized in a medium-term focus in V4, which means that there is a certain lag between monetary policy operation and its influence on an inflation target. Central bank does not have a direct impact on its ultimate goals. Therefore, any monetary policy analysis and assumption of its effectiveness comes out from an essential existence of a working transmission mechanism. Thus, changes in settings of monetary policy instruments have to be able to inflict causal changes on intermediary markets and via these markets on target markets. This situation can be modeled by the vector autoregressive (VAR model with suitable variables. Our main task is to compare a relationship between VAR model responses to predefined impulses for all V4 pairs. We use calibration technique for this purpose. Specifically, we will utilize one-dimensional calibration model with a linear calibration function for deriving unknown parameters. Moreover, we will test a significance of estimated parameters. We distinguish between model parameters for before-crisis- and during-crisis- data, because we suppose that financial crisis affects VAR model parameters significantly. Different responses in each country can mean the inability of the common monetary policy for V4 at present.

  17. Predictive spatio-temporal model for spatially sparse global solar radiation data

    International Nuclear Information System (INIS)

    André, Maïna; Dabo-Niang, Sophie; Soubdhan, Ted; Ould-Baba, Hanany

    2016-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at a located station for very short time scale. We built a multivariate model in using few stations (3 stations) separated with irregular distances from 26 km to 56 km. The proposed model is a spatio temporal vector autoregressive VAR model specifically designed for the analysis of spatially sparse spatio-temporal data. This model differs from classic linear models in using spatial and temporal parameters where the available predictors are the lagged values at each station. A spatial structure of stations is defined by the sequential introduction of predictors in the model. Moreover, an iterative strategy in the process of our model will select the necessary stations removing the uninteresting predictors and also selecting the optimal p-order. We studied the performance of this model. The metric error, the relative root mean squared error (rRMSE), is presented at different short time scales. Moreover, we compared the results of our model to simple and well known persistence model and those found in literature. - Highlights: • A spatio-temporal VAR forecast model is used for spatially sparse data solar. • Lags and locations are selected by an optimization strategy. • Definition of spatial ordering of predictors influences forecasting results. • The model shows a better performance predictive at 30 min ahead in our context. • Benchmarking study shows a more accurate forecast at 1 h ahead with spatio-temporal VAR.

  18. Haavelmo's Probability Approach and the Cointegrated VAR

    DEFF Research Database (Denmark)

    Juselius, Katarina

    Some key econometric concepts and problems addressed by Trygve Haavelmo and Ragnar Frisch are discussed within the general frame- work of a cointegrated VAR. The focus is on problems typical of time- series data such as multicollinearity, spurious correlation and regres- sion results, time......) the plausibility of the multivari- ate normality assumption underlying the VAR, (3) cointegration as a solution to the problem of spurious correlation and multicollinearity when data contain deterministic and stochastic trends, (4) the exis- tence of a universe, (5) the association between Frisch’s con...

  19. Comparison of historically simulated VaR: Evidence from oil prices

    International Nuclear Information System (INIS)

    Costello, Alexandra; Asem, Ebenezer; Gardner, Eldon

    2008-01-01

    Cabedo and Moya [Cabedo, J.D., Moya, I., 2003. Estimating oil price 'Value at Risk' using the historical simulation approach. Energy Economics 25, 239-253] find that ARMA with historical simulation delivers VaR forecasts that are superior to those from GARCH. We compare the ARMA with historical simulation to the semi-parametric GARCH model proposed by Barone-Adesi et al. [Barone-Adesi, G., Giannopoulos, K., Vosper, L., 1999. VaR without correlations for portfolios of derivative securities. Journal of Futures Markets 19 (5), 583-602]. The results suggest that the semi-parametric GARCH model generates VaR forecasts that are superior to the VaR forecasts from the ARMA with historical simulation. This is due to the fact that GARCH captures volatility clustering. Our findings suggest that Cabedo and Moya's conclusion is mainly driven by the normal distributional assumption imposed on the future risk structure in the GARCH model. (author)

  20. A Two-Factor Autoregressive Moving Average Model Based on Fuzzy Fluctuation Logical Relationships

    Directory of Open Access Journals (Sweden)

    Shuang Guan

    2017-10-01

    Full Text Available Many of the existing autoregressive moving average (ARMA forecast models are based on one main factor. In this paper, we proposed a new two-factor first-order ARMA forecast model based on fuzzy fluctuation logical relationships of both a main factor and a secondary factor of a historical training time series. Firstly, we generated a fluctuation time series (FTS for two factors by calculating the difference of each data point with its previous day, then finding the absolute means of the two FTSs. We then constructed a fuzzy fluctuation time series (FFTS according to the defined linguistic sets. The next step was establishing fuzzy fluctuation logical relation groups (FFLRGs for a two-factor first-order autoregressive (AR(1 model and forecasting the training data with the AR(1 model. Then we built FFLRGs for a two-factor first-order autoregressive moving average (ARMA(1,m model. Lastly, we forecasted test data with the ARMA(1,m model. To illustrate the performance of our model, we used real Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX and Dow Jones datasets as a secondary factor to forecast TAIEX. The experiment results indicate that the proposed two-factor fluctuation ARMA method outperformed the one-factor method based on real historic data. The secondary factor may have some effects on the main factor and thereby impact the forecasting results. Using fuzzified fluctuations rather than fuzzified real data could avoid the influence of extreme values in historic data, which performs negatively while forecasting. To verify the accuracy and effectiveness of the model, we also employed our method to forecast the Shanghai Stock Exchange Composite Index (SHSECI from 2001 to 2015 and the international gold price from 2000 to 2010.

  1. Comparison of Classical and Robust Estimates of Threshold Auto-regression Parameters

    Directory of Open Access Journals (Sweden)

    V. B. Goryainov

    2017-01-01

    Full Text Available The study object is the first-order threshold auto-regression model with a single zero-located threshold. The model describes a stochastic temporal series with discrete time by means of a piecewise linear equation consisting of two linear classical first-order autoregressive equations. One of these equations is used to calculate a running value of the temporal series. A control variable that determines the choice between these two equations is the sign of the previous value of the same series.The first-order threshold autoregressive model with a single threshold depends on two real parameters that coincide with the coefficients of the piecewise linear threshold equation. These parameters are assumed to be unknown. The paper studies an estimate of the least squares, an estimate the least modules, and the M-estimates of these parameters. The aim of the paper is a comparative study of the accuracy of these estimates for the main probabilistic distributions of the updating process of the threshold autoregressive equation. These probability distributions were normal, contaminated normal, logistic, double-exponential distributions, a Student's distribution with different number of degrees of freedom, and a Cauchy distribution.As a measure of the accuracy of each estimate, was chosen its variance to measure the scattering of the estimate around the estimated parameter. An estimate with smaller variance made from the two estimates was considered to be the best. The variance was estimated by computer simulation. To estimate the smallest modules an iterative weighted least-squares method was used and the M-estimates were done by the method of a deformable polyhedron (the Nelder-Mead method. To calculate the least squares estimate, an explicit analytic expression was used.It turned out that the estimation of least squares is best only with the normal distribution of the updating process. For the logistic distribution and the Student's distribution with the

  2. Antisense long noncoding RNAs regulate var gene activation in the malaria parasite Plasmodium falciparum.

    Science.gov (United States)

    Amit-Avraham, Inbar; Pozner, Guy; Eshar, Shiri; Fastman, Yair; Kolevzon, Netanel; Yavin, Eylon; Dzikowski, Ron

    2015-03-03

    The virulence of Plasmodium falciparum, the causative agent of the deadliest form of human malaria, is attributed to its ability to evade human immunity through antigenic variation. These parasites alternate between expression of variable antigens, encoded by members of a multicopy gene family named var. Immune evasion through antigenic variation depends on tight regulation of var gene expression, ensuring that only a single var gene is expressed at a time while the rest of the family is maintained transcriptionally silent. Understanding how a single gene is chosen for activation is critical for understanding mutually exclusive expression but remains a mystery. Here, we show that antisense long noncoding RNAs (lncRNAs) initiating from var introns are associated with the single active var gene at the time in the cell cycle when the single var upstream promoter is active. We demonstrate that these antisense transcripts are incorporated into chromatin, and that expression of these antisense lncRNAs in trans triggers activation of a silent var gene in a sequence- and dose-dependent manner. On the other hand, interference with these lncRNAs using complement peptide nucleic acid molecules down-regulated the active var gene, erased the epigenetic memory, and induced expression switching. Altogether, our data provide evidence that these antisense lncRNAs play a key role in regulating var gene activation and mutually exclusive expression.

  3. Forecasting systems reliability based on support vector regression with genetic algorithms

    International Nuclear Information System (INIS)

    Chen, K.-Y.

    2007-01-01

    This study applies a novel neural-network technique, support vector regression (SVR), to forecast reliability in engine systems. The aim of this study is to examine the feasibility of SVR in systems reliability prediction by comparing it with the existing neural-network approaches and the autoregressive integrated moving average (ARIMA) model. To build an effective SVR model, SVR's parameters must be set carefully. This study proposes a novel approach, known as GA-SVR, which searches for SVR's optimal parameters using real-value genetic algorithms, and then adopts the optimal parameters to construct the SVR models. A real reliability data for 40 suits of turbochargers were employed as the data set. The experimental results demonstrate that SVR outperforms the existing neural-network approaches and the traditional ARIMA models based on the normalized root mean square error and mean absolute percentage error

  4. Mosquito Passage Dramatically Changes var Gene Expression in Controlled Human Plasmodium falciparum Infections.

    Science.gov (United States)

    Bachmann, Anna; Petter, Michaela; Krumkamp, Ralf; Esen, Meral; Held, Jana; Scholz, Judith A M; Li, Tao; Sim, B Kim Lee; Hoffman, Stephen L; Kremsner, Peter G; Mordmüller, Benjamin; Duffy, Michael F; Tannich, Egbert

    2016-04-01

    Virulence of the most deadly malaria parasite Plasmodium falciparum is linked to the variant surface antigen PfEMP1, which is encoded by about 60 var genes per parasite genome. Although the expression of particular variants has been associated with different clinical outcomes, little is known about var gene expression at the onset of infection. By analyzing controlled human malaria infections via quantitative real-time PCR, we show that parasite populations from 18 volunteers expressed virtually identical transcript patterns that were dominated by the subtelomeric var gene group B and, to a lesser extent, group A. Furthermore, major changes in composition and frequency of var gene transcripts were detected between the parental parasite culture that was used to infect mosquitoes and Plasmodia recovered from infected volunteers, suggesting that P. falciparum resets its var gene expression during mosquito passage and starts with the broad expression of a specific subset of var genes when entering the human blood phase.

  5. Genome-wide analysis of SU(VAR)3-9 distribution in chromosomes of Drosophila melanogaster.

    Science.gov (United States)

    Maksimov, Daniil A; Laktionov, Petr P; Posukh, Olga V; Belyakin, Stepan N; Koryakov, Dmitry E

    2018-03-01

    Histone modifications represent one of the key factors contributing to proper genome regulation. One of histone modifications involved in gene silencing is methylation of H3K9 residue. Present in the chromosomes across different eukaryotes, this epigenetic mark is controlled by SU(VAR)3-9 and its orthologs. Despite SU(VAR)3-9 was discovered over two decades ago, little is known about the details of its chromosomal distribution pattern. To fill in this gap, we used DamID-seq approach and obtained high-resolution genome-wide profiles for SU(VAR)3-9 in two somatic (salivary glands and brain ganglia) and two germline (ovarian nurse cells and testes) tissues of Drosophila melanogaster. Analysis of tissue and developmental expression of SU(VAR)3-9-bound genes indicates that in the somatic tissues tested, as well as in the ovarian nurse cells, SU(VAR)3-9 tends to associate with transcriptionally silent genes. In contrast, in the testes, SU(VAR)3-9 shows preferential association with testis-specific genes, and its binding appears dynamic during spermatogenesis. In somatic cells, the mere presence/absence of SU(VAR)3-9 binding correlates with lower/higher expression. No such correlation is found in the male germline. Interestingly, transcription units in piRNA clusters (particularly flanks thereof) are frequently targeted by SU(VAR)3-9, and Su(var)3-9 mutation affects the expression of select piRNA species. Our analyses suggest a context-dependent role of SU(VAR)3-9. In euchromatin, SU(VAR)3-9 may serve to fine-tune the expression of individual genes, whereas in heterochromatin, chromosome 4, and piRNA clusters, it may act more broadly over large chromatin domains.

  6. Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

    Science.gov (United States)

    Wang, Qijie

    2015-08-01

    The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

  7. Twenty novel polymorphic microsatellite primers in the critically endangered Melastoma tetramerum var. tetramerum (Melastomataceae).

    Science.gov (United States)

    Narita, Ayu; Izuno, Ayako; Komaki, Yoshiteru; Tanaka, Takefumi; Murata, Jin; Isagi, Yuji

    2016-09-01

    Microsatellite markers were identified for Melastoma tetramerum var. tetramerum (Melastomataceae), a critically endangered shrub endemic to the Bonin Islands, to reveal genetic characteristics in wild and restored populations. Using next-generation sequencing, 27 microsatellite markers were identified. Twenty of these markers were polymorphic in M. tetramerum var. tetramerum, with two to nine alleles per locus and expected heterozygosity ranging from 0.10 to 0.71. Among the 20 polymorphic markers, 15 were applicable to other closely related taxa, namely M. tetramerum var. pentapetalum, M. candidum var. candidum, and M. candidum var. alessandrense. These markers can be potentially useful to investigate the genetic diversity, population genetic structure, and reproductive ecology of M. tetramerum var. tetramerum as well as of the three related taxa to provide appropriate genetic information for conservation.

  8. Semi-nonparametric VaR forecasts for hedge funds during the recent crisis

    Science.gov (United States)

    Del Brio, Esther B.; Mora-Valencia, Andrés; Perote, Javier

    2014-05-01

    The need to provide accurate value-at-risk (VaR) forecasting measures has triggered an important literature in econophysics. Although these accurate VaR models and methodologies are particularly demanded for hedge fund managers, there exist few articles specifically devoted to implement new techniques in hedge fund returns VaR forecasting. This article advances in these issues by comparing the performance of risk measures based on parametric distributions (the normal, Student’s t and skewed-t), semi-nonparametric (SNP) methodologies based on Gram-Charlier (GC) series and the extreme value theory (EVT) approach. Our results show that normal-, Student’s t- and Skewed t- based methodologies fail to forecast hedge fund VaR, whilst SNP and EVT approaches accurately success on it. We extend these results to the multivariate framework by providing an explicit formula for the GC copula and its density that encompasses the Gaussian copula and accounts for non-linear dependences. We show that the VaR obtained by the meta GC accurately captures portfolio risk and outperforms regulatory VaR estimates obtained through the meta Gaussian and Student’s t distributions.

  9. Identifying the impacts of climate on the regional transport of haze pollution and inter-cities correspondence within the Yangtze River Delta.

    Science.gov (United States)

    Xiao, Hang; Huang, Zhongwen; Zhang, Jingjing; Zhang, Huiling; Chen, Jinsheng; Zhang, Han; Tong, Lei

    2017-09-01

    Regional haze pollution has become an important environmental issue in the Yangtze River Delta (YRD) region. Regional transport and inter-influence of PM 2.5 among cities occurs frequently as a result of the subtropical monsoon climate. Backward trajectory statistics indicated that a north wind prevailed from October to March, while a southeast wind predominated from May to September. The temporal relationships of carbon and nitrogen isotopes among cities were dependent on the prevailing wind direction. Regional PM 2.5 pollution was confirmed in the YRD region by means of significant correlations and similar cyclical characteristics of PM 2.5 among Lin'an, Ningbo, Nanjing and Shanghai. Granger causality tests of the time series of PM 2.5 values indicate that the regional transport of haze pollutants is governed by prevailing wind direction, as the PM 2.5 concentrations from upwind area cities generally influence that of the downwind cities. Furthermore, stronger correlation coefficients were identified according to monsoon pathways. To clarify the impacts of the monsoon climate, a vector autoregressive (VAR) model was introduced. Variance decomposition in the VAR model also indicated that the upwind area cities contributed significantly to PM 2.5 in the downwind area cities. Finally, we attempted to predict daily PM 2.5 concentrations in each city based on the VAR model using data from all cities and obtained fairly reasonable predictions. These indicate that statistical methods of the Granger causality test and VAR model have the potential to evaluate inter-influence and the relative contribution of PM 2.5 among cities, and to predict PM 2.5 concentrations as well. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Comparative anatomy of the leaves of Piper lepturum(Kunth) C.DC. var. lepturum and Piper lepturum var. angustifolium (C.DC.) Yunck.

    OpenAIRE

    Machado, Nelson Santana de Oliveira; Pereira, Flaviane Gomes; Santos, Paulo Roberto Dias dos; Costa, Cecília Gonçalves; Guimarães, Elsie Franklin

    2015-01-01

    This study showed anatomical differences related to Piper lepturumvar. lepturum and P. lepturum var. angustifolium species, sometimes considered varieties and in other cases synonyms. For histological analysis, fully expanded leaves were collected and for analysis by scanning electron microscope (SEM), fragments from the midrib were fixed on both leaf surfaces. The two species revealed differences in plant anatomy and it was observed that the stem of P. lepturum var. lepturum showed persisten...

  11. Testing the Conditional Mean Function of Autoregressive Conditional Duration Models

    DEFF Research Database (Denmark)

    Hautsch, Nikolaus

    be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor......This paper proposes a dynamic proportional hazard (PH) model with non-specified baseline hazard for the modelling of autoregressive duration processes. A categorization of the durations allows us to reformulate the PH model as an ordered response model based on extreme value distributed errors...

  12. On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets

    International Nuclear Information System (INIS)

    Benth, Fred Espen; Taib, Che Mohd Imran Che

    2013-01-01

    We extend the concept of half life of an Ornstein–Uhlenbeck process to Lévy-driven continuous-time autoregressive moving average processes with stochastic volatility. The half life becomes state dependent, and we analyze its properties in terms of the characteristics of the process. An empirical example based on daily temperatures observed in Petaling Jaya, Malaysia, is presented, where the proposed model is estimated and the distribution of the half life is simulated. The stationarity of the dynamics yield futures prices which asymptotically tend to constant at an exponential rate when time to maturity goes to infinity. The rate is characterized by the eigenvalues of the dynamics. An alternative description of this convergence can be given in terms of our concept of half life. - Highlights: • The concept of half life is extended to Levy-driven continuous time autoregressive moving average processes • The dynamics of Malaysian temperatures are modeled using a continuous time autoregressive model with stochastic volatility • Forward prices on temperature become constant when time to maturity tends to infinity • Convergence in time to maturity is at an exponential rate given by the eigenvalues of the model temperature model

  13. Drought Patterns Forecasting using an Auto-Regressive Logistic Model

    Science.gov (United States)

    del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

    2014-12-01

    Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

  14. Resistance to Southern Root-knot Nematode (Meloidogyne incognita) in Wild Watermelon (Citrullus lanatus var. citroides).

    Science.gov (United States)

    Thies, Judy A; Ariss, Jennifer J; Kousik, Chandrasekar S; Hassell, Richard L; Levi, Amnon

    2016-03-01

    Southern root-knot nematode (RKN, Meloidogyne incognita) is a serious pest of cultivated watermelon (Citrullus lanatus var. lanatus) in southern regions of the United States and no resistance is known to exist in commercial watermelon cultivars. Wild watermelon relatives (Citrullus lanatus var. citroides) have been shown in greenhouse studies to possess varying degrees of resistance to RKN species. Experiments were conducted over 2 yr to assess resistance of southern RKN in C. lanatus var. citroides accessions from the U.S. Watermelon Plant Introduction Collection in an artificially infested field site at the U.S. Vegetable Laboratory in Charleston, SC. In the first study (2006), 19 accessions of C. lanatus var. citroides were compared with reference entries of Citrullus colocynthis and C. lanatus var. lanatus. Of the wild watermelon accessions, two entries exhibited significantly less galling than all other entries. Five of the best performing C. lanatus var. citroides accessions were evaluated with and without nematicide at the same field site in 2007. Citrullus lanatus var. citroides accessions performed better than C. lanatus var. lanatus and C. colocynthis. Overall, most entries of C. lanatus var. citroides performed similarly with and without nematicide treatment in regard to root galling, visible egg masses, vine vigor, and root mass. In both years of field evaluations, most C. lanatus var. citroides accessions showed lesser degrees of nematode reproduction and higher vigor and root mass than C. colocynthis and C. lanatus var. lanatus. The results of these two field evaluations suggest that wild watermelon populations may be useful sources of resistance to southern RKN.

  15. ESTIMATING RISK ON THE CAPITAL MARKET WITH VaR METHOD

    Directory of Open Access Journals (Sweden)

    Sinisa Bogdan

    2015-06-01

    Full Text Available The two basic questions that every investor tries to answer before investment are questions about predicting return and risk. Risk and return are generally considered two positively correlated sizes, during the growth of risk it is expected increase of return to compensate the higher risk. The quantification of risk in the capital market represents the current topic since occurrence of securities. Together with estimated future returns it represents starting point of any investment. In this study it is described the history of the emergence of VaR methods, usefulness in assessing the risks of financial assets. Three main Value at Risk (VaR methodologies are decribed and explained in detail: historical method, parametric method and Monte Carlo method. After the theoretical review of VaR methods it is estimated risk of liquid stocks and portfolio from the Croatian capital market with historical and parametric VaR method, after which the results were compared and explained.

  16. Comparison of historically simulated VaR: Evidence from oil prices

    Energy Technology Data Exchange (ETDEWEB)

    Costello, Alexandra [Seminole Canada Energy, Calgary, AB (Canada); Asem, Ebenezer; Gardner, Eldon [Faculty of Management, University of Lethbridge, Lethbridge, AB (Canada)

    2008-09-15

    Cabedo and Moya [Cabedo, J.D., Moya, I., 2003. Estimating oil price 'Value at Risk' using the historical simulation approach. Energy Economics 25, 239-253] find that ARMA with historical simulation delivers VaR forecasts that are superior to those from GARCH. We compare the ARMA with historical simulation to the semi-parametric GARCH model proposed by Barone-Adesi et al. [Barone-Adesi, G., Giannopoulos, K., Vosper, L., 1999. VaR without correlations for portfolios of derivative securities. Journal of Futures Markets 19 (5), 583-602]. The results suggest that the semi-parametric GARCH model generates VaR forecasts that are superior to the VaR forecasts from the ARMA with historical simulation. This is due to the fact that GARCH captures volatility clustering. Our findings suggest that Cabedo and Moya's conclusion is mainly driven by the normal distributional assumption imposed on the future risk structure in the GARCH model. (author)

  17. PREVALENCIA DE Strongyloides stercoralis Y OTROS PARÁSITOS INTESTINALES EN INDIGENTES ALCOHÓLICOS DE CIUDAD BOLÍVAR, ESTADO BOLÍVAR, VENEZUELA | PREVALENCE OF Strongyloides stercoralis AND OTHER INTESTINAL PARASITES IN ALCOHOLIC HOMELESS FROM CIUDAD BOLÍVAR, BOLÍVAR STATE, VENEZUELA

    Directory of Open Access Journals (Sweden)

    Rodolfo Devera

    2015-11-01

    Full Text Available Between may and july 2010 a study was performed in order to determine the prevalence of Strongyloides stercoralis and other intestinal parasites in alcoholic homeless who attend two Alcoholics Anonymous Centers in Ciudad Bolívar, Bolívar State, Venezuela. Eighty stool samples were collected, which were analyzed using the techniques of direct examination, Kato, micro-Baermann, Rugai and agar plate culture. An estimate of 61.3% of the evaluated population was parasitized. The intestinal parasite most prevalent was the chromist Blastocystis (33.8%. Among the protozoan, the most common was Endolimax nana (21.3% and among the helminths it was Strongyloides stercoralis (12.5%.

  18. Da abort ikke var en sag for kvinden

    DEFF Research Database (Denmark)

    Schultz, Annette Østergaard

    2013-01-01

    Case fra tiden før 1973, hvor der ikke var fri abort i Danmark. Sagen er fundet i Mødrehjælpens arkiv og giver som andre sager indblik i kvindens situation. Led i serien: Nyt i arkivet.......Case fra tiden før 1973, hvor der ikke var fri abort i Danmark. Sagen er fundet i Mødrehjælpens arkiv og giver som andre sager indblik i kvindens situation. Led i serien: Nyt i arkivet....

  19. Optimizing expression of the pregnancy malaria vaccine candidate, VAR2CSA in Pichia pastoris.

    Science.gov (United States)

    Avril, Marion; Hathaway, Marianne J; Cartwright, Megan M; Gose, Severin O; Narum, David L; Smith, Joseph D

    2009-06-29

    VAR2CSA is the main candidate for a vaccine against pregnancy-associated malaria, but vaccine development is complicated by the large size and complex disulfide bonding pattern of the protein. Recent X-ray crystallographic information suggests that domain boundaries of VAR2CSA Duffy binding-like (DBL) domains may be larger than previously predicted and include two additional cysteine residues. This study investigated whether longer constructs would improve VAR2CSA recombinant protein secretion from Pichia pastoris and if domain boundaries were applicable across different VAR2CSA alleles. VAR2CSA sequences were bioinformatically analysed to identify the predicted C11 and C12 cysteine residues at the C-termini of DBL domains and revised N- and C-termimal domain boundaries were predicted in VAR2CSA. Multiple construct boundaries were systematically evaluated for protein secretion in P. pastoris and secreted proteins were tested as immunogens. From a total of 42 different VAR2CSA constructs, 15 proteins (36%) were secreted. Longer construct boundaries, including the predicted C11 and C12 cysteine residues, generally improved expression of poorly or non-secreted domains and permitted expression of all six VAR2CSA DBL domains. However, protein secretion was still highly empiric and affected by subtle differences in domain boundaries and allelic variation between VAR2CSA sequences. Eleven of the secreted proteins were used to immunize rabbits. Antibodies reacted with CSA-binding infected erythrocytes, indicating that P. pastoris recombinant proteins possessed native protein epitopes. These findings strengthen emerging data for a revision of DBL domain boundaries in var-encoded proteins and may facilitate pregnancy malaria vaccine development.

  20. Optimizing expression of the pregnancy malaria vaccine candidate, VAR2CSA in Pichia pastoris

    Directory of Open Access Journals (Sweden)

    Narum David L

    2009-06-01

    Full Text Available Abstract Background VAR2CSA is the main candidate for a vaccine against pregnancy-associated malaria, but vaccine development is complicated by the large size and complex disulfide bonding pattern of the protein. Recent X-ray crystallographic information suggests that domain boundaries of VAR2CSA Duffy binding-like (DBL domains may be larger than previously predicted and include two additional cysteine residues. This study investigated whether longer constructs would improve VAR2CSA recombinant protein secretion from Pichia pastoris and if domain boundaries were applicable across different VAR2CSA alleles. Methods VAR2CSA sequences were bioinformatically analysed to identify the predicted C11 and C12 cysteine residues at the C-termini of DBL domains and revised N- and C-termimal domain boundaries were predicted in VAR2CSA. Multiple construct boundaries were systematically evaluated for protein secretion in P. pastoris and secreted proteins were tested as immunogens. Results From a total of 42 different VAR2CSA constructs, 15 proteins (36% were secreted. Longer construct boundaries, including the predicted C11 and C12 cysteine residues, generally improved expression of poorly or non-secreted domains and permitted expression of all six VAR2CSA DBL domains. However, protein secretion was still highly empiric and affected by subtle differences in domain boundaries and allelic variation between VAR2CSA sequences. Eleven of the secreted proteins were used to immunize rabbits. Antibodies reacted with CSA-binding infected erythrocytes, indicating that P. pastoris recombinant proteins possessed native protein epitopes. Conclusion These findings strengthen emerging data for a revision of DBL domain boundaries in var-encoded proteins and may facilitate pregnancy malaria vaccine development.

  1. Waarnemingen aan Equisetum arvense L. var. serotinum F.W. Meyer

    NARCIS (Netherlands)

    Hoek, van L.

    1978-01-01

    Observations during six successive years in a cultivated clone of Equisetum arvense L. var. serotinum F. W. Meyer made it possible to study various types of fertile, sterile, and homophyadic stems developing in this clone. As E. arvense var. varium Milde, E. arvense f. sanguineum Luerss., and E.

  2. Een nieuwe naam voor Arenaria serpyllifolia L. var. macrocarpa Lloyd

    NARCIS (Netherlands)

    Gutermann, W.; Mennema, J.

    1983-01-01

    The name Arenaria serpyllifoiia L. var. macrocarpa Lloyd is illegitimate, because of the existence of the earlier non-synonymous A. serpyllifolia0 macrocarpa Godron. As on the level of variety no other name is available, we call the taxon A renaria serpylli/olia L. var. Iloydn (Jord.) Gutermann et

  3. THE GRANGER CAUSALITY TESTS FOR THE FIVE ASEAN COUNTRIES STOCK MARKETS AND MACROECONOMIC VARIABLES DURING AND POST THE 1997 ASIAN FINANCIAL CRISIS

    Directory of Open Access Journals (Sweden)

    Adwin Surja Atmadja

    2005-01-01

    Full Text Available This study seeks to examine the existence of Granger-causality among stock prices indices and macroeconomic variables in five ASEAN countries, Indonesia; Malaysia; the Philippines; Singapore; and Thailand with particular attention to the 1997 Asian financial crisis and period onwards. Using monthly time series data of the countries, a Granger-causality test based on the vector autoregressive (VAR analytical framework was employed to empirically reveal the causality among the variables. This research finds that there were few Granger causalities found between the country's wtock price index and macroeconomic variables. This indicates that the linkages between domestic stock price movements and macroeconomic factors were very. Due to that, the ASEAN stock markets were crelatively unable to efficiently capture changes in economic fundamentals during the observation period in most of the countries in accordance to the literature in emerging stock markets, and that the influence of specific macroeconomic factors on the domestic economies differ across countries. This also implies that the stock markets do not seem to have played a significant role in most countries' economies, and macroeconomic variables are unlikely to be appropriate indicators to predict not only the future behaviour of other macroeconomic variables, but also that of the stock market price indices. Abstract in Bahasa Indonesia : Makalah ini mencoba untuk menganalisis keberadaan Granger-causality antara indeks harga saham dan variabel-variabel ekonomi makro di lima negara ASEAN, yaitu Indonesia; Malaysia; Filipina; Singapore; dan Thailand yang berfokus pada periode terjadinya krisis keuangan Asia pada tahun 1997 dan sesudahnya. Dengan mempergunakan data time series bulanan dari setiap negara tersebut, tes Granger-causality yang didasarkan pada kerangka analisa VAR (vector autoregressive diaplikasikan untuk mengungkap secara empiris hubungan kausal antar variabel. Dari hasil tes

  4. Exact eigenstates and open-quotes trivialityclose quotes of λ(var-phi *var-phi)2 theory in the Feshbach-Villars formulation

    International Nuclear Information System (INIS)

    Darewych, J.W.

    1997-01-01

    The complex scalar (Klein-Gordon) quantum field theory (QFT) with a λ(var-phi * var-phi) 2 interaction is considered in the Feshbach-Villars formulation. It is shown that exact few-particle eigenstates of the QFT Hamiltonian can be obtained. The resulting relativistic few-body equations correspond to Klein-Gordon particles interacting via delta-function, or open-quotes contact,close quotes potentials. Momentum-space solutions of the two-body equation yield a open-quotes trivialclose quotes unity S matrix. copyright 1997 The American Physical Society

  5. Phyllactinia mali and Podosphaera tridactyla var. tridactyla – new hosts of Ampelomyces quisqualis

    Directory of Open Access Journals (Sweden)

    Beata Czerniawska

    2014-08-01

    Full Text Available In 2002, the occurrence of fungi of the order Erysiphales on plants of the Słowiański Park located in Goorzów Wielkopolski was investigated. Plant samples were collected once a month, from August to November. The samples examined were above ground plant parts colonized by powdery mildew fungi. A total of 78 samples were collected. Apart from 14 species of the order Erysiphales, Ampelomyces quisqualis parasitizing on Erysiphe cichoracearum var. cichoracearum, Phyllactinia mali and Podosphaera tridactyl var. tridactyla was found. Ampelomyces quisqualis affected hyphae, oidia, and young cleistothecia of P. mali. In contrast, in E. cichoracearum var. cichoracearum, Po. tridactyle var. tridactyla, this hyperparasite colonized only hyphae and oidia. This paper for the first trime informs of A. quisqualis parasitizing on P. mali and Po. tridactyla var. tridactyla.

  6. "Var Teatre"--A Pioneer Turns 40.

    Science.gov (United States)

    Jones, Pamela L.

    1984-01-01

    Describes the Stockholm Municipal Youth and Children's theatre ("Var Teatre"), an institution of 14 theatres and attendant professional staff devoted exclusively to drama activities for children and teenagers. (PD)

  7. Estimating temporary and permanent stock price innovations on Croatian capital market

    Directory of Open Access Journals (Sweden)

    Tihana Škrinjarić

    2014-03-01

    Full Text Available This paper evaluates the size and duration of temporary and permanent stock price innovations on Croatian capital market in the structural VAR (vector autoregression framework with Blanchard and Quah (1989 decomposition. The purpose is to identify the effects of temporary price innovations in order to determine to which extent future stock prices can be predicted. Temporary components present in stock prices are explained throughout the mean-reversion hypothesis. This means that stock prices deviate from the fundamental values, but they will revert to their mean. In that way, to some extent, it is possible to predict future price movements. The results show that for the observed period from January 2000 to September 2013, temporary innovations account for only 2.62% of price variability over a two-year horizon. This means that forecasting the future movements of stock prices on Zagreb Stock Exchange is a difficult task.

  8. Competitiveness and Economic Growth in Romanian Regions

    Directory of Open Access Journals (Sweden)

    Simionescu Mihaela

    2016-12-01

    Full Text Available Considering the fact that Romanian economy competitiveness is not based on innovation and investment in human capital, this study makes an empirical evaluation of the impact of occupation and unemployment in Romanian counties on the economic growth. The approach based on panel vector-autoregressive (panel VAR models indicated a negative impact of occupation and activity rate in 42 Romanian counties on the economic growth during 2006-2014. On the other hand, the real economic growth was achieved at high unemployment rates. These results are contrary to previous studies in literature and are due to a structural economic crisis and to lack of labour productivity and investment in human capital. Further policy measures should focus on structural unemployment decrease, more skilled labour force according to labour market needs, lifelong learning, higher performance and quality of education system, promotion of social inclusion, poverty control.

  9. Wavelet decomposition and regime shifts. Assessing the effects of crude oil shocks on stock market returns

    Energy Technology Data Exchange (ETDEWEB)

    Jammazi, Rania; Aloui, Chaker [International finance group-Tunisia, Faculty of Management and Economic Sciences of Tunis, Boulevard du 7 novembre, El Manar University, B.P. 248, C.P. 2092, Tunis Cedex (Tunisia)

    2010-03-15

    While there is a large body of empirical studies on the relationship between crude oil price changes and stock market returns, they have failed to achieve a consensus on this subject. In this paper, we combine wavelet analysis and Markov Switching Vector Autoregressive (MS-VAR) approach to explore the impact of the crude oil (CO) shocks on the stock market returns for UK, France and Japan over the period from January 1989 to December 2007. Our procedure involves the estimation of the extended MS-VAR model in order to investigate the importance of the resultant wavelet filtering series (after removing random components) in determining the behavior of the stock market volatilities. We show that CO shocks do not affect the recession stock market phases (except for Japan). However, they significantly reduce moderate and/or expansion stock market phases temporarily. Moreover, this negative relationship appears to be more pronounced during the pre-1999 period. The empirical findings will prove extremely useful to investors who need to understand the exact effect of international oil changes on certain stocks prices as well as for policy managers who need a more thorough evaluation about the efficiency of hedging policies affected by oil price changes. (author)

  10. Wavelet decomposition and regime shifts: Assessing the effects of crude oil shocks on stock market returns

    Energy Technology Data Exchange (ETDEWEB)

    Jammazi, Rania, E-mail: jamrania2@yahoo.f [International finance group-Tunisia, Faculty of Management and Economic Sciences of Tunis, Boulevard du 7 novembre, El Manar University, B.P. 248, C.P. 2092, Tunis Cedex (Tunisia); Aloui, Chaker, E-mail: chaker.aloui@fsegt.rnu.t [International finance group-Tunisia, Faculty of Management and Economic Sciences of Tunis, Boulevard du 7 novembre, El Manar University, B.P. 248, C.P. 2092, Tunis Cedex (Tunisia)

    2010-03-15

    While there is a large body of empirical studies on the relationship between crude oil price changes and stock market returns, they have failed to achieve a consensus on this subject. In this paper, we combine wavelet analysis and Markov Switching Vector Autoregressive (MS-VAR) approach to explore the impact of the crude oil (CO) shocks on the stock market returns for UK, France and Japan over the period from January 1989 to December 2007. Our procedure involves the estimation of the extended MS-VAR model in order to investigate the importance of the resultant wavelet filtering series (after removing random components) in determining the behavior of the stock market volatilities. We show that CO shocks do not affect the recession stock market phases (except for Japan). However, they significantly reduce moderate and/or expansion stock market phases temporarily. Moreover, this negative relationship appears to be more pronounced during the pre-1999 period. The empirical findings will prove extremely useful to investors who need to understand the exact effect of international oil changes on certain stocks prices as well as for policy managers who need a more thorough evaluation about the efficiency of hedging policies affected by oil price changes.

  11. Wavelet decomposition and regime shifts: Assessing the effects of crude oil shocks on stock market returns

    International Nuclear Information System (INIS)

    Jammazi, Rania; Aloui, Chaker

    2010-01-01

    While there is a large body of empirical studies on the relationship between crude oil price changes and stock market returns, they have failed to achieve a consensus on this subject. In this paper, we combine wavelet analysis and Markov Switching Vector Autoregressive (MS-VAR) approach to explore the impact of the crude oil (CO) shocks on the stock market returns for UK, France and Japan over the period from January 1989 to December 2007. Our procedure involves the estimation of the extended MS-VAR model in order to investigate the importance of the resultant wavelet filtering series (after removing random components) in determining the behavior of the stock market volatilities. We show that CO shocks do not affect the recession stock market phases (except for Japan). However, they significantly reduce moderate and/or expansion stock market phases temporarily. Moreover, this negative relationship appears to be more pronounced during the pre-1999 period. The empirical findings will prove extremely useful to investors who need to understand the exact effect of international oil changes on certain stocks prices as well as for policy managers who need a more thorough evaluation about the efficiency of hedging policies affected by oil price changes.

  12. Somatic Embryogenesis in Olive (Olea europaea L. subsp. europaea var. sativa and var. sylvestris).

    Science.gov (United States)

    Rugini, Eddo; Silvestri, Cristian

    2016-01-01

    Protocols for olive somatic embryogenesis from zygotic embryos and mature tissues have been described for both Olea europaea sub. europaea var. sativa and var. sylvestris. Immature zygotic embryos (no more than 75 days old), used after fruit collection or stored at 12-14 °C for 2-3 months, are the best responsive explants and very slightly genotype dependent, and one single protocol can be effective for a wide range of genotypes. On the contrary, protocols for mature zygotic embryos and for mature tissue of cultivars are often genotype specific, so that they may require many adjustments according to genotypes. The use of thidiazuron and cefotaxime seems to be an important trigger for induction phase particularly for tissues derived from cultivars. Up to now, however, the application of this technique for large-scale propagation is hampered also by the low rate of embryo germination; it proves nonetheless very useful for genetic improvement.

  13. VAR Portfolio Optimal: Perbandingan Antara Metode Markowitz dan Mean Absolute Deviation

    Directory of Open Access Journals (Sweden)

    R. Agus Sartono

    2009-05-01

    Full Text Available Portfolio selection method which have been introduced by Harry Markowitz (1952 used variance or deviation standard as a measure of risk. Kanno and Yamazaki (1991 introduced another method and used mean absolute deviation as a measure of risk instead of variance. The Value-at Risk (VaR is a relatively new method to capitalized risk that been used by financial institutions. The aim of this research is compare between mean variance and mean absolute deviation of two portfolios. Next, we attempt to assess the VaR of two portfolios using delta normal method and historical simulation. We use the secondary data from the Jakarta Stock Exchange – LQ45 during 2003. We find that there is a weak-positive correlation between deviation standard and return in both portfolios. The VaR nolmal delta based on mean absolute deviation method eventually is higher than the VaR normal delta based on mean variance method. However, based on the historical simulation the VaR of two methods is statistically insignificant. Thus, the deviation standard is sufficient measures of portfolio risk.Keywords: optimalisasi portofolio, mean-variance, mean-absolute deviation, value-at-risk, metode delta normal, metode simulasi historis

  14. Dynamics of anti-VAR2CSA immunoglobulin G response in a cohort of senegalese pregnant women

    DEFF Research Database (Denmark)

    Tuikue Ndam, N G; Salanti, A; Le-Hesran, J-Y

    2006-01-01

    demonstrated that a single P. falciparum infection was able to trigger a VAR2CSA-specific antibody response. Among women with infected placentas, women with high anti-VAR2CSA IgG levels at enrollment were more likely to present with a past infection than with an acute/chronic infection. CONCLUSIONS: Anti-VAR2...... (VSAPAM). Several studies have shown that 1 var gene, var2csa, is transcribed at high levels and expressed in CSA-binding Plasmodium falciparum parasites. METHODS: Plasma levels of anti-VAR2CSA immunoglobulin G (IgG) in Senegalese women were measured during pregnancy by enzyme-linked immunosorbent assay......, using 3 recombinant proteins representing 3 domains of the var2csa gene product. RESULTS: The 3 recombinant proteins were specifically recognized by plasma from pregnant women but not by control plasma. A parity-dependent recognition pattern was observed with 2 of the 3 VAR2CSA antigens. A kinetic study...

  15. Murine Model for Preclinical Studies of Var2CSA-Mediated Pathology Associated with Malaria in Pregnancy

    Science.gov (United States)

    Dechavanne, Sebastien; Sousa, Patrícia M.; Barateiro, André; Cunha, Sónia F.; Nunes-Silva, Sofia; Lima, Flávia A.; Murillo, Oscar; Marinho, Claudio R. F.; Gangnard, Stephane; Srivastava, Anand; Braks, Joanna A.; Janse, Chris J.; Gamain, Benoit; Penha-Gonçalves, Carlos

    2016-01-01

    Plasmodium falciparum infection during pregnancy leads to abortions, stillbirth, low birth weight, and maternal mortality. Infected erythrocytes (IEs) accumulate in the placenta by adhering to chondroitin sulfate A (CSA) via var2CSA protein exposed on the P. falciparum IE membrane. Plasmodium berghei IE infection in pregnant BALB/c mice is a model for severe placental malaria (PM). Here, we describe a transgenic P. berghei parasite expressing the full-length var2CSA extracellular region (domains DBL1X to DBL6ε) fused to a P. berghei exported protein (EMAP1) and characterize a var2CSA-based mouse model of PM. BALB/c mice were infected at midgestation with different doses of P. berghei-var2CSA (P. berghei-VAR) or P. berghei wild-type IEs. Infection with 104 P. berghei-VAR IEs induced a higher incidence of stillbirth and lower fetal weight than P. berghei. At doses of 105 and 106 IEs, P. berghei-VAR-infected mice showed increased maternal mortality during pregnancy and fetal loss, respectively. Parasite loads in infected placentas were similar between parasite lines despite differences in maternal outcomes. Fetal weight loss normalized for parasitemia was higher in P. berghei-VAR-infected mice than in P. berghei-infected mice. In vitro assays showed that higher numbers of P. berghei-VAR IEs than P. berghei IEs adhered to placental tissue. Immunization of mice with P. berghei-VAR elicited IgG antibodies reactive to DBL1-6 recombinant protein, indicating that the topology of immunogenic epitopes is maintained between DBL1-6–EMAP1 on P. berghei-VAR and recombinant DBL1-6 (recDBL1-6). Our data suggested that impairments in pregnancy caused by P. berghei-VAR infection were attributable to var2CSA expression. This model provides a tool for preclinical evaluation of protection against PM induced by approaches that target var2CSA. PMID:27045035

  16. A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market

    DEFF Research Database (Denmark)

    Hurn, A.S.; Silvennoinen, Annastiina; Teräsvirta, Timo

    We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting of specific......We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting...... of specification, including testing linearity, estimation and evaluation of these models is constructed. Nonlinear least squares estimation of the parameters of the model is discussed. Evaluation by misspecification tests is carried out using tests derived in a companion paper. The use of the modelling strategy...

  17. Fast Responding Voltage Regulator and Dynamic VAR Compensator

    Energy Technology Data Exchange (ETDEWEB)

    Divan, Deepak [Varentec, Incorporated, San Jose, CA (United States); Moghe, Rohit [Varentec, Incorporated, San Jose, CA (United States); Tholomier, Damien [Varentec, Incorporated, San Jose, CA (United States)

    2014-12-31

    The objectives of this project were to develop a dynamic VAR compensator (DVC) for voltage regulation through VAR support to demonstrate the ability to achieve greater levels of voltage control on electricity distribution networks, and faster response compared to existing grid technology. The goal of the project was to develop a prototype Fast Dynamic VAR Compensator (Fast DVC) hardware device, and this was achieved. In addition to developing the dynamic VAR compensator device, Varentec in partnership with researchers at North Carolina State University (NCSU) successfully met the objectives to model the potential positive impact of such DVCs on representative power networks. This modeling activity validated the ability of distributed dynamic VAR compensators to provide fast voltage regulation and reactive power control required to respond to grid disturbances under high penetration of fluctuating and intermittent distributed energy resources (DERs) through extensive simulation studies. Specifically the following tasks were set to be accomplished: 1) Development of dynamic VAR compensator to support dynamic voltage variations on the grid through VAR control 2) Extensive testing of the DVC in the lab environment 3) Present the operational DVC device to the DOE at Varentec’s lab 4) Formulation of a detailed specification sheet, unit assembly document, test setup document, unit bring-up plan, and test plan 5) Extensive simulations of the DVC in a system with high PV penetration. Understanding the operation with many DVC on a single distribution system 6) Creation and submittal of quarterly and final reports conveying the design documents, unit performance data, modeling simulation charts and diagrams, and summary explanations of the satisfaction of program goals. This report details the various efforts that led to the development of the Fast DVC as well as the modeling & simulation results. The report begins with the introduction in Section II which outlines the

  18. Saccharomyces cerevisiae var. boulardii fungemia following probiotic treatment

    Directory of Open Access Journals (Sweden)

    Marcelo C. Appel-da-Silva

    2017-12-01

    Full Text Available Probiotics are commonly prescribed as an adjuvant in the treatment of antibiotic-associated diarrhea caused by Clostridium difficile. We report the case of an immunocompromised 73-year-old patient on chemotherapy who developed Saccharomyces cerevisiae var. boulardii fungemia in a central venous catheter during treatment of antibiotic-associated pseudomembranous colitis with the probiotic Saccharomyces cerevisiae var. boulardii. Fungemia was resolved after interruption of probiotic administration without the need to replace the central venous line. Keywords: Saccharomyces, Probiotics, Fungemia, Critical illness, Clostridium difficile

  19. On the relationship between health, education and economic growth: Time series evidence from Malaysia

    Science.gov (United States)

    Khan, Habib Nawaz; Razali, Radzuan B.; Shafei, Afza Bt.

    2016-11-01

    The objectives of this paper is two-fold: First, to empirically investigate the effects of an enlarged number of healthy and well-educated people on economic growth in Malaysia within the Endogeneous Growth Model framework. Second, to examine the causal links between education, health and economic growth using annual time series data from 1981 to 2014 for Malaysia. Data series were checked for the time series properties by using ADF and KPSS tests. Long run co-integration relationship was investigated with the help of vector autoregressive (VAR) method. For short and long run dynamic relationship investigation vector error correction model (VECM) was applied. Causality analysis was performed through Engle-Granger technique. The study results showed long run co-integration relation and positively significant effects of education and health on economic growth in Malaysia. The reported results also confirmed a feedback hypothesis between the variables in the case of Malaysia. The study results have policy relevance of the importance of human capital (health and education) to the growth process of the Malaysia. Thus, it is suggested that policy makers focus on education and health sectors for sustainable economic growth in Malaysia.

  20. Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations

    KAUST Repository

    Yan, Yuan

    2017-11-20

    When performing a time series analysis of continuous data, for example from climate or environmental problems, the assumption that the process is Gaussian is often violated. Therefore, we introduce two non-Gaussian autoregressive time series models that are able to fit skewed and heavy-tailed time series data. Our two models are based on the Tukey g-and-h transformation. We discuss parameter estimation, order selection, and forecasting procedures for our models and examine their performances in a simulation study. We demonstrate the usefulness of our models by applying them to two sets of wind speed data.

  1. Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations

    KAUST Repository

    Yan, Yuan; Genton, Marc G.

    2017-01-01

    When performing a time series analysis of continuous data, for example from climate or environmental problems, the assumption that the process is Gaussian is often violated. Therefore, we introduce two non-Gaussian autoregressive time series models that are able to fit skewed and heavy-tailed time series data. Our two models are based on the Tukey g-and-h transformation. We discuss parameter estimation, order selection, and forecasting procedures for our models and examine their performances in a simulation study. We demonstrate the usefulness of our models by applying them to two sets of wind speed data.

  2. The Effect of Macroeconomic Variables on Value-Added Agriculture: Approach of Vector Autoregresive Bayesian Model (BVAR

    Directory of Open Access Journals (Sweden)

    E. Pishbahar

    2015-05-01

    Full Text Available There are different ideas and opinions about the effects of macroeconomic variables on real and nominal variables. To answer the question of whether changes in macroeconomic variables as a political tool is useful over a business cycle, understanding the effect of macroeconomic variables on economic growth is important. In the present study, the Bayesian Vector autoregresive model and seasonality data for the years between 1991 and 2013 was used to determine the impact of monetary policy on value-added agriculture. Predicts of Vector autoregresive model are usually divertaed due to a lot of parameters in the model. Bayesian vector autoregresive model estimates more reliable predictions due to reducing the number of included parametrs and considering the former models. Compared to the Vector Autoregressive model, the coefficients are estimated more accurately. Based on the results of RMSE in this study, previous function Nrmal-Vyshart was identified as a suitable previous disteribution. According to the results of the impulse response function, the sudden effects of shocks in macroeconomic variables on the value added in agriculture and domestic venture capital are stable. The effects on the exchange rates, tax revenues and monetary will bemoderated after 7, 5 and 4periods. Monetary policy shocks ,in the first half of the year, increased the value added of agriculture, while in the second half of the year had a depressing effect on the value added.

  3. Asymptotically stable phase synchronization revealed by autoregressive circle maps

    Science.gov (United States)

    Drepper, F. R.

    2000-11-01

    A specially designed of nonlinear time series analysis is introduced based on phases, which are defined as polar angles in spaces spanned by a finite number of delayed coordinates. A canonical choice of the polar axis and a related implicit estimation scheme for the potentially underlying autoregressive circle map (next phase map) guarantee the invertibility of reconstructed phase space trajectories to the original coordinates. The resulting Fourier approximated, invertibility enforcing phase space map allows us to detect conditional asymptotic stability of coupled phases. This comparatively general synchronization criterion unites two existing generalizations of the old concept and can successfully be applied, e.g., to phases obtained from electrocardiogram and airflow recordings characterizing cardiorespiratory interaction.

  4. The Influence of Sub-Unit Composition and Expression System on the Functional Antibody Response in the Development of a VAR2CSA Based Plasmodium falciparum Placental Malaria Vaccine.

    Directory of Open Access Journals (Sweden)

    Morten A Nielsen

    Full Text Available The disease caused by Plasmodium falciparum (Pf involves different clinical manifestations that, cumulatively, kill hundreds of thousands every year. Placental malaria (PM is one such manifestation in which Pf infected erythrocytes (IE bind to chondroitin sulphate A (CSA through expression of VAR2CSA, a parasite-derived antigen. Protection against PM is mediated by antibodies that inhibit binding of IE in the placental intervillous space. VAR2CSA is a large antigen incompatible with large scale recombinant protein expression. Vaccines based on sub-units encompassing the functionally constrained receptor-binding domains may, theoretically, circumvent polymorphisms, reduce the risk of escape-mutants and induce cross-reactive antibodies. However, the sub-unit composition and small differences in the borders, may lead to exposure of novel immuno-dominant antibody epitopes that lead to non-functional antibodies, and furthermore influence the folding, stability and yield of expression. Candidate antigens from the pre-clinical development expressed in High-Five insect cells using the baculovirus expression vector system were transitioned into the Drosophila Schneider-2 cell (S2 expression-system compliant with clinical development. The functional capacity of antibodies against antigens expressed in High-Five cells or in S2 cells was equivalent. This enabled an extensive down-selection of S2 insect cell-expressed antigens primarily encompassing the minimal CSA-binding region of VAR2CSA. In general, we found differential potency of inhibitory antibodies against antigens with the same borders but of different var2csa sequences. Likewise, we found that subtle size differences in antigens of the same sequence gave varying levels of inhibitory antibodies. The study shows that induction of a functional response against recombinant subunits of the VAR2CSA antigen is unpredictable, demonstrating the need for large-scale screening in order to identify antigens

  5. Computing Conditional VaR using Time-varying CopulasComputing Conditional VaR using Time-varying Copulas

    Directory of Open Access Journals (Sweden)

    Beatriz Vaz de Melo Mendes

    2005-12-01

    Full Text Available It is now widespread the use of Value-at-Risk (VaR as a canonical measure at risk. Most accurate VaR measures make use of some volatility model such as GARCH-type models. However, the pattern of volatility dynamic of a portfolio follows from the (univariate behavior of the risk assets, as well as from the type and strength of the associations among them. Moreover, the dependence structure among the components may change conditionally t past observations. Some papers have attempted to model this characteristic by assuming a multivariate GARCH model, or by considering the conditional correlation coefficient, or by incorporating some possibility for switches in regimes. In this paper we address this problem using time-varying copulas. Our modeling strategy allows for the margins to follow some FIGARCH type model while the copula dependence structure changes over time.

  6. An introduction to vectors, vector operators and vector analysis

    CERN Document Server

    Joag, Pramod S

    2016-01-01

    Ideal for undergraduate and graduate students of science and engineering, this book covers fundamental concepts of vectors and their applications in a single volume. The first unit deals with basic formulation, both conceptual and theoretical. It discusses applications of algebraic operations, Levi-Civita notation, and curvilinear coordinate systems like spherical polar and parabolic systems and structures, and analytical geometry of curves and surfaces. The second unit delves into the algebra of operators and their types and also explains the equivalence between the algebra of vector operators and the algebra of matrices. Formulation of eigen vectors and eigen values of a linear vector operator are elaborated using vector algebra. The third unit deals with vector analysis, discussing vector valued functions of a scalar variable and functions of vector argument (both scalar valued and vector valued), thus covering both the scalar vector fields and vector integration.

  7. MODEL NON LINIER GARCH (NGARCH UNTUK MENGESTIMASI NILAI VALUE at RISK (VaR PADA IHSG

    Directory of Open Access Journals (Sweden)

    I KOMANG TRY BAYU MAHENDRA

    2015-06-01

    Full Text Available In investment, risk measurement is important. One of risk measure is Value at Risk (VaR. There are many methods that can be used to estimate risk based on VaR framework. One of them Non Linier GARCH (NGARCH model. In this research, determination of VaR used NGARCH model. NGARCH model allowed for asymetric behaviour in the volatility such that “good news” or positive return and “bad news” or negative return. Based on calculations of VaR, the higher of the confidence level and the longer the investment period, the risk was greater. Determination of VaR using NGARCH model was less than GARCH model.

  8. On the link between oil price and exchange rate: A time-varying VAR parameter approach

    International Nuclear Information System (INIS)

    Bremond, Vincent; Razafindrabe, Tovonony; Hache, Emmanuel

    2015-07-01

    The aim of this paper is to study the relationship between the effective exchange rate of the dollar and the oil price dynamics from 1976 to 2013. In this context, we propose to explore the economic literature dedicated to financial channels factors (exchange rate, monetary policy, and international liquidity) that could affect the oil price dynamics. In addition to oil prices and the effective exchange rate of the dollar, we use the dry cargo index as a proxy for the real economic activity and prices for precious and industrial raw materials. Using a Bayesian time-varying parameter vector auto-regressive estimation, our main results show that the US Dollar effective exchange rate elasticity of the crude oil prices is not constant across the time and remains negative from 1989. It then highlights that a depreciation of the effective exchange rate of the dollar leads to an increase of the crude oil prices. Our paper also demonstrates the growing influence of financial and commodities markets development upon the global economy. (authors)

  9. [Gene cloning and bioinformatics analysis of SABATH methyltransferase in Lonicera japonica var. chinensis].

    Science.gov (United States)

    Yu, Xiao-Dan; Jiang, Chao; Huang, Lu-Qi; Qin, Shuang-Shuang; Zeng, Xiang-Mei; Chen, Ping; Yuan, Yuan

    2013-08-01

    To clone SABATH methyltransferase (rLjSABATHMT) gene in Lonicera japonica var. chinensis, and compare the gene expression and intron sequence of SABATH methyltransferase orthologous in L. japonica with L. japonica var. chinensis. It provide a basis for gene regulate the formation of L. japonica floral scents. The cDNA and genome sequences of LjSABATHMT from L. japonica var. chinensis were cloned according to the gene fragments in cDNA library. The LjSABATHMT protein was characterized by bioinformatics analysis. SABATH family phylogenetic tree were built by MEGA 5.0. The transcripted level of SABATHMT orthologous were analyzed in different organs and different flower periods of L. japonica and L. japonica var. chinensis using RT-PCR analysis. Intron sequences of SABATHMT orthologous were also analyzied. The cDNA of LjSABATHMT was 1 251 bp, had a complete coding frame with 365 amino acids. The protein had the conservative SABATHMT domain, and phylogenetic tree showed that it may be a salicylic acid/benzoic acid methyltransferase. Higher expression of SABATH methyltransferase orthologous was found in flower. The intron sequence of L. japonica and L. japonica var. chinensis had rich polymorphism, and two SNP are unique genotype of L. japonica var. chinensis. The motif elements in two orthologous genes were significant differences. The intron difference of SABATH methyltransferase orthologous could be inducing to difference of gene expression between L. japonica and L. japonica var. chinensis. These results will provide important base on regulating active compounds of L. japonica.

  10. A hybrid PSO technique for procuring VAR ancillary service in the deregulated electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    El-Araby, E.E. [Department of Electrical Engineering, Suez Canal University (Egypt); Yorino, Naoto [Department of Artificial Complex Systems Engineering, Hiroshima University (Japan)

    2010-07-15

    This paper develops a new market-based technique for acquiring VAR ancillary service in the electricity market. The main objective of the developed market is to enable transmission operator ''TO'' to procure VAR service in a long term contract from the critical VAR providers that satisfy minimum VAR service payment while maintaining system security. Reactive power control problem for voltage stability is introduced into the VAR market problem in an explicit manner for normal and emergency states. An integration of particle swarm optimization ''PSO'' is presented with successive linear programming ''SLP'' for dealing with the VAR ancillary service problem. The problem is formulated as a large-scale nonlinear constrained optimization problem with a non-differentiable objective function representing VAR payment and operational costs. This type of problem is hard to be treated straightforwardly by the classical optimization methods. Therefore, we propose here a two-layer hybrid PSO/SLP approach, which is suited for carrying out the difficulties associated with non-differentiable and discontinuous objective functions. The proposed method has been examined on the standard IEEE 57 bus-system and compared with GA/SLP method to demonstrate its capability. (author)

  11. Product development projects dynamics and emergent complexity

    CERN Document Server

    Schlick, Christopher

    2016-01-01

    This book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dyn...

  12. Insurance penetration and economic growth in Africa: Dynamic effects analysis using Bayesian TVP-VAR approach

    Directory of Open Access Journals (Sweden)

    D.O. Olayungbo

    2016-12-01

    Full Text Available This paper examines the dynamic interactions between insurance and economic growth in eight African countries for the period of 1970–2013. Insurance demand is measured by insurance penetration which accounts for income differences across the sample countries. A Bayesian Time Varying Parameter Vector Auto regression (TVP-VAR model with stochastic volatility is used to analyze the short run and the long run among the variables of interest. Using insurance penetration as a measure of insurance to economic growth, we find positive relationship for Egypt, while short-run negative and long-run positive effects are found for Kenya, Mauritius, and South Africa. On the contrary, negative effects are found for Algeria, Nigeria, Tunisia, and Zimbabwe. Implementation of sound financial reforms and wide insurance coverage are proposed recommendations for insurance development in the selected African countries.

  13. Arundina graminifolia var. revoluta (Arethuseae, Orchidaceae) has fern-type rheophyte characteristics in the leaves.

    Science.gov (United States)

    Yorifuji, Eri; Ishikawa, Naoko; Okada, Hiroshi; Tsukaya, Hirokazu

    2015-03-01

    Morphological and molecular variation between Arundina graminifolia var. graminifolia and the dwarf variety, A. graminifolia var. revoluta, was examined to assess the validity of their taxonomic characteristics and genetic background for identification. Morphological analysis in combination with field observations indicated that A. graminifolia var. revoluta is a rheophyte form of A. graminifolia characterized by narrow leaves, whereas the other morphological characteristics described for A. graminifolia var. revoluta, such as smaller flowers and short stems, were not always accompanied by the narrower leaf phenotype. Molecular analysis based on matK sequences indicated that only partial differentiation has occurred between A. graminifolia var. graminifolia and A. graminifolia var. revoluta. Therefore, we should consider the rheophyte form an ecotype rather than a variety. Anatomical observations of the leaves revealed that the rheophyte form of A. graminifolia possessed characteristics of the rheophytes of both ferns and angiosperms, such as narrower palisade tissue cells and thinner spongy tissue cells, as well as fewer cells in the leaf-width direction and fewer mesophyll cell layers.

  14. Robust estimation of autoregressive processes using a mixture-based filter-bank

    Czech Academy of Sciences Publication Activity Database

    Šmídl, V.; Anthony, Q.; Kárný, Miroslav; Guy, Tatiana Valentine

    2005-01-01

    Roč. 54, č. 4 (2005), s. 315-323 ISSN 0167-6911 R&D Projects: GA AV ČR IBS1075351; GA ČR GA102/03/0049; GA ČR GP102/03/P010; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian estimation * probabilistic mixtures * recursive estimation Subject RIV: BC - Control Systems Theory Impact factor: 1.239, year: 2005 http://library.utia.cas.cz/separaty/historie/karny-robust estimation of autoregressive processes using a mixture-based filter- bank .pdf

  15. An orientin derivative isolated from Passiflora tripartita var. mollissima

    OpenAIRE

    Ramos, Freddy A.; Castellanos, Leonardo; López, César; Palacios, Lizeth; Duque, Carmenza; Pacheco, Ricardo; Guzmán, Antonio

    2010-01-01

    Passiflora tripartita var. mollisima (banana passion fruit) is an edible fruit widespread in the Andean highlands of Colombia and Ecuador. The fruit is used for juices as well as for the sedative properties of the leaves. As a contribution to the chemical characterization of this species, a new compound, 4'- methoxyluteolin-8-C-6”acetylglucopyranoside, was isolated from the ethanolic extract of Passiflora tripartita var. mollisima leaves and identified by spectroscopical data (NMR, MS, UV).

  16. Plasmodium falciparum var Gene Silencing Is Determined by cis DNA Elements That Form Stable and Heritable Interactions ▿

    Science.gov (United States)

    Swamy, Lakshmi; Amulic, Borko; Deitsch, Kirk W.

    2011-01-01

    Antigenic variation in the human malaria parasite Plasmodium falciparum depends on the transcriptional regulation of the var gene family. In each individual parasite, mRNA is expressed exclusively from 1 var gene out of ∼60, while the rest of the genes are transcriptionally silenced. Both modifications to chromatin structure and DNA regulatory elements associated with each var gene have been implicated in the organization and maintenance of the silent state. Whether silencing is established at the level of entire chromosomal regions via heterochromatin spreading or at the level of individual var promoters through the action of a silencing element within each var intron has been debated. Here, we consider both possibilities, using clonal parasite lines carrying chromosomally integrated transgenes. We confirm a previous finding that the loss of an adjacent var intron results in var promoter activation and further show that transcriptional activation of a var promoter within a cluster does not affect the transcriptional activity of neighboring var promoters. Our results provide more evidence for the hypothesis that var genes are primarily silenced at the level of an individual gene, rather than by heterochromatin spreading. We also tested the intrinsic directionality of an intron's silencing effect on upstream or downstream var promoters. We found that an intron is capable of silencing in either direction and that, once established, a var promoter-intron pair is stably maintained through many generations, suggesting a possible role in epigenetic memory. This study provides insights into the regulation of endogenous var gene clusters. PMID:21317310

  17. Can reported VaR be used as an indicator of the volatility of share prices? Evidence from UK banks.

    OpenAIRE

    Ou, Shian Kao

    2006-01-01

    Value at Risk (VaR) is used as an indicator to measure the risks contained in a firm. With the uprising development of VaR theory and computational techniques, the VaR is nowadays adopted by banks and reported in annual reports. Since the method to calculate VaR is questioned, and the reported VaR can not be thoroughly audited, this paper attempts to find the relationship between the reported VaR and the volatility of share price for UK listed banks. This paper reviews literature about VaR an...

  18. A novel virus-like particle based vaccine platform displaying the placental malaria antigen VAR2CSA

    DEFF Research Database (Denmark)

    Thrane, Susan; Janitzek, Christoph M; Agerbæk, Mette Ø

    2015-01-01

    , this difference was not statistically significant after 3rd immunization. Importantly, the VLP-VAR2CSA induced antibodies were functional in inhibiting the binding of parasites to CSA. This study demonstrates that the described Avi-L1 VLP-platform may serve as a versatile system for facilitating optimal VLP......SA-VAR2CSA vaccines induced higher antibody titers than the soluble naked VAR2CSA vaccine after three immunizations. The VAR2CSA Avi-L1 VLP vaccine induced statistically significantly higher endpoint titres compared to the soluble mSA-VAR2CSA vaccine, after 1st and 2nd immunization; however...

  19. Population genomics of the immune evasion (var genes of Plasmodium falciparum.

    Directory of Open Access Journals (Sweden)

    Alyssa E Barry

    2007-03-01

    Full Text Available Var genes encode the major surface antigen (PfEMP1 of the blood stages of the human malaria parasite Plasmodium falciparum. Differential expression of up to 60 diverse var genes in each parasite genome underlies immune evasion. We compared the diversity of the DBLalpha domain of var genes sampled from 30 parasite isolates from a malaria endemic area of Papua New Guinea (PNG and 59 from widespread geographic origins (global. Overall, we obtained over 8,000 quality-controlled DBLalpha sequences. Within our sampling frame, the global population had a total of 895 distinct DBLalpha "types" and negligible overlap among repertoires. This indicated that var gene diversity on a global scale is so immense that many genomes would need to be sequenced to capture its true extent. In contrast, we found a much lower diversity in PNG of 185 DBLalpha types, with an average of approximately 7% overlap among repertoires. While we identify marked geographic structuring, nearly 40% of types identified in PNG were also found in samples from different countries showing a cosmopolitan distribution for much of the diversity. We also present evidence to suggest that recombination plays a key role in maintaining the unprecedented levels of polymorphism found in these immune evasion genes. This population genomic framework provides a cost effective molecular epidemiological tool to rapidly explore the geographic diversity of var genes.

  20. Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

    Science.gov (United States)

    Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

    2017-01-01

    Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

  1. Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

    Science.gov (United States)

    Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

    2017-08-01

    Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

  2. Sporozoite Route of Infection Influences In Vitro var Gene Transcription of Plasmodium falciparum Parasites From Controlled Human Infections.

    Science.gov (United States)

    Dimonte, Sandra; Bruske, Ellen I; Hass, Johanna; Supan, Christian; Salazar, Carmen L; Held, Jana; Tschan, Serena; Esen, Meral; Flötenmeyer, Matthias; Koch, Iris; Berger, Jürgen; Bachmann, Anna; Sim, Betty K L; Hoffman, Stephen L; Kremsner, Peter G; Mordmüller, Benjamin; Frank, Matthias

    2016-09-15

    Antigenic variation in Plasmodium falciparum is mediated by the multicopy var gene family. Each parasite possesses about 60 var genes, and switching between active var loci results in antigenic variation. In the current study, the effect of mosquito and host passage on in vitro var gene transcription was investigated. Thirty malaria-naive individuals were inoculated by intradermal or intravenous injection with cryopreserved, isogenic NF54 P. falciparum sporozoites (PfSPZ) generated from 1 premosquito culture. Microscopic parasitemia developed in 22 individuals, and 21 in vitro cultures were established. The var gene transcript levels were determined in early and late postpatient cultures and in the premosquito culture. At the early time point, all cultures preferentially transcribed 8 subtelomeric var genes. Intradermal infections had higher var gene transcript levels than intravenous infections and a significantly longer intrahost replication time (P = .03). At the late time point, 9 subtelomeric and 8 central var genes were transcribed at the same levels in almost all cultures. Premosquito and late postpatient cultures transcribed the same subtelomeric and central var genes, except for var2csa  The duration of intrahost replication influences in vitro var gene transcript patterns. Differences between premosquito and postpatient cultures decrease with prolonged in vitro growth. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

  3. Disruption of var2csa gene impairs placental malaria associated adhesion phenotype.

    Directory of Open Access Journals (Sweden)

    Nicola K Viebig

    Full Text Available Infection with Plasmodium falciparum during pregnancy is one of the major causes of malaria related morbidity and mortality in newborn and mothers. The complications of pregnancy-associated malaria result mainly from massive adhesion of Plasmodium falciparum-infected erythrocytes (IE to chondroitin sulfate A (CSA present in the placental intervillous blood spaces. Var2CSA, a member of the P. falciparum erythrocyte membrane protein 1 (PfEMP1 family is the predominant parasite ligand mediating CSA binding. However, experimental evidence suggests that other host receptors, such as hyaluronic acid (HA and the neonatal Fc receptor, may also support placental binding. Here we used parasites in which var2csa was genetically disrupted to evaluate the contribution of these receptors to placental sequestration and to identify additional adhesion receptors that may be involved in pregnancy-associated malaria. By comparison to the wild-type parasites, the FCR3delta var2csa mutants could not be selected for HA adhesion, indicating that var2csa is not only essential for IE cytoadhesion to the placental receptor CSA, but also to HA. However, further studies using different pure sources of HA revealed that the previously observed binding results from CSA contamination in the bovine vitreous humor HA preparation. To identify CSA-independent placental interactions, FCR3delta var2csa mutant parasites were selected for adhesion to the human placental trophoblastic BeWo cell line. BeWo selected parasites revealed a multi-phenotypic adhesion population expressing multiple var genes. However, these parasites did not cytoadhere specifically to the syncytiotrophoblast lining of placental cryosections and were not recognized by sera from malaria-exposed women in a parity dependent manner, indicating that the surface molecules present on the surface of the BeWo selected population are not specifically expressed during the course of pregnancy-associated malaria. Taken

  4. Does animal-mediated seed dispersal facilitate the formation of Pinus armandii-Quercus aliena var. acuteserrata forests?

    Science.gov (United States)

    Yu, Fei; Wang, Dexiang; Yi, Xianfeng; Shi, Xiaoxiao; Huang, Yakun; Zhang, Hongwu; Zhang, XinPing

    2014-01-01

    The Pinus armandii and Quercus aliena var. acuteserrata mixed forest is one of the major forest types in the Qinling Mountains, China. P. armandii is considered to be a pioneer species during succession and it is usually invaded by late successional Q. aliena var. acuteserrata. However, the mechanism that underlies its invasion remains unclear. In the present study, we tracked seed dispersal of P. armandii and Q. aliena var. acuteserrata using coded plastic tags in the western, middle and eastern Qinling Mountains to elucidate the invasion process in the mixed forests. Our results indicated that the seeds of both P. armandii and Q. aliena var. acuteserrata were removed rapidly in the Qinling Mountains, and there were no differences in the seed removal rates between the two species. There were significant differences in rodent seed-eating and caching strategies between the two tree species. For P. armandii, seeds were more likely to be eaten in situ than those of Q. aliena var. acuteserrata in all plots. By contrast, the acorns of Q. aliena var. acuteserrata were less frequently eaten in situ, but more likely to be removed and cached. Q. aliena var. acuteserrata acorns had significantly longer dispersal distances than P. armandii seeds in all plots. Although P. armandii seeds were less likely to be dispersed into the Q. aliena var. acuteserrata stands, over 30% of the released acorns were transported into the P. armandii stands where they established five seedlings. Based on the coupled recruitment patterns of P. armandii and Q. aliena var. acuteserrata, we suggest that the animal-mediated seed dispersal contributes to the formation of Pinus armandii-Quercus aliena var. acuteserrata forests.

  5. PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO

    Directory of Open Access Journals (Sweden)

    WAYAN ARTHINI

    2012-09-01

    Full Text Available Value at Risk (VaR is the maximum potential loss on a portfolio based on the probability at a certain time.  In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data. Historical data is processed so as to obtain stock returns, variance, correlation coefficient, and variance-covariance matrix, then the method of Markowitz sought proportion of each stock fund, and portfolio risk and return portfolio. The data was then simulated by Monte Carlo simulation, Exact Monte Carlo Simulation and Expected Monte Carlo Simulation. Exact Monte Carlo simulation have same returns and standard deviation  with historical data, while the Expected Monte Carlo Simulation satistic calculation similar to historical data. The results of this research is the portfolio VaR  with time horizon T=1, T=10, T=22 and the confidence level of 95 %, values obtained VaR between historical data and Monte Carlo simulation data with the method exact and expected. Value of VaR from both Monte Carlo simulation is greater than VaR historical data.

  6. Generation of antigenic diversity in Plasmodium falciparum by structured rearrangement of Var genes during mitosis.

    Science.gov (United States)

    Claessens, Antoine; Hamilton, William L; Kekre, Mihir; Otto, Thomas D; Faizullabhoy, Adnan; Rayner, Julian C; Kwiatkowski, Dominic

    2014-12-01

    The most polymorphic gene family in P. falciparum is the ∼60 var genes distributed across parasite chromosomes, both in the subtelomeres and in internal regions. They encode hypervariable surface proteins known as P. falciparum erythrocyte membrane protein 1 (PfEMP1) that are critical for pathogenesis and immune evasion in Plasmodium falciparum. How var gene sequence diversity is generated is not currently completely understood. To address this, we constructed large clone trees and performed whole genome sequence analysis to study the generation of novel var gene sequences in asexually replicating parasites. While single nucleotide polymorphisms (SNPs) were scattered across the genome, structural variants (deletions, duplications, translocations) were focused in and around var genes, with considerable variation in frequency between strains. Analysis of more than 100 recombination events involving var exon 1 revealed that the average nucleotide sequence identity of two recombining exons was only 63% (range: 52.7-72.4%) yet the crossovers were error-free and occurred in such a way that the resulting sequence was in frame and domain architecture was preserved. Var exon 1, which encodes the immunologically exposed part of the protein, recombined in up to 0.2% of infected erythrocytes in vitro per life cycle. The high rate of var exon 1 recombination indicates that millions of new antigenic structures could potentially be generated each day in a single infected individual. We propose a model whereby var gene sequence polymorphism is mainly generated during the asexual part of the life cycle.

  7. [Correlation between distribution of rhizospheric microorganisms and contents of steroidal saponins of Paris polyphylla var. yunnanensis].

    Science.gov (United States)

    Zhou, Nong; Qi, Wen-hua; Xiao, Guo-sheng; Ding, Bo; Zhang, Hua; Guo, Dong-qin; Shen, Wei

    2015-03-01

    In this paper, the varying pattern of the amount of rhizospheric microorganisms, including bacteria, actinomycetes and fungus, was observed during the cultivation of Paris polyphylla var. yunnanensis. And the correlations between number of rhizospheric microorganisms and the quality of P. polyphylla var. yunnanensis were also studied. The results showed that the rhizospheric microorganism source of P. polyphylla var. yunnanensis was rich. The distribution of rhizospheric microorganisms (soil bacteria, fungus, actinomycetes, potassium-solubilizing bacteria, inorganic phosphorus-solubilizing bacteria, organic phosphorus-solubilizing bacteria) collected from different origin places existed significant difference (P the amount of actinomycetes > the amount of fungus. The medicinal quality of P. polyphylla var. yunnanensis was influenced by their habits, and the increase of cultivation years caused the obvious decrease of the quality of P. polyphylla var. yunnanensis. Therefore, the increase of cultivation years will cause the variation of the soil micro-ecology flora, and decrease the nutrient absorption and the utilization of P. polyphylla var. yunnanensis, which will make the decrease of the medical quality of P. polyphylla var. yunnanensis.

  8. Upport vector machines for nonlinear kernel ARMA system identification.

    Science.gov (United States)

    Martínez-Ramón, Manel; Rojo-Alvarez, José Luis; Camps-Valls, Gustavo; Muñioz-Marí, Jordi; Navia-Vázquez, Angel; Soria-Olivas, Emilio; Figueiras-Vidal, Aníbal R

    2006-11-01

    Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA2K) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based system identification nonlinear models is presented, based on the use of composite Mercer's kernels. This general class can improve model flexibility by emphasizing the input-output cross information (SVM-ARMA4K), which leads to straightforward and natural combinations of implicit and explicit ARMA models (SVR-ARMA2K and SVR-ARMA4K). Capabilities of these different SVM-based system identification schemes are illustrated with two benchmark problems.

  9. Monetary policy and regional output in Brazil

    Directory of Open Access Journals (Sweden)

    Rafael Rockenbach da Silva Guimarães

    2014-03-01

    Full Text Available This work presents an analysis of whether the effects of the Brazilian monetary policy on regional outputs are symmetric. The strategy developed combines the techniques of principal component analysis (PCA to decompose the variables that measure regional economic activity into common and region-specific components and vector autoregressions (VAR to observe the behavior of these variables in response to monetary policy shocks. The common component responds to monetary policy as expected. Additionally, the idiosyncratic components of the regions showed no impact of monetary policy. The main finding of this paper is that the monetary policy responses on regional output are symmetrical when the regional output decomposition is performed, and the responses are asymmetrical when this decomposition is not performed. Therefore, performing the regional output decomposition corroborates the economic intuition that monetary policy has no impact on region-specific issues. Once monetary policy affects the common component of the regional economic activity and does not impact its idiosyncratic components, it can be considered symmetrical.

  10. Monetary Policy and Financial Asset Prices: Empirical Evidence from Pakistan

    Directory of Open Access Journals (Sweden)

    Imran Umer Chhapra

    2018-03-01

    Full Text Available Monetary transmission mechanism assumed to be significantly influenced by the effect of policy decisions on financial markets. However, various previous studies have come up with different outcomes. The purpose of this study is to examine the impact of monetary policy on different asset classes (shares and bonds in Pakistan. This study using stock price and bond yield as dependent variable and discount rate, money supply, inflation, and exchange rate are independent variables. Data of all variables have collected from 2010 to 2016, and Vector Autoregressive (VAR technique has applied. The empirical results indicate that there is an impact of monetary policy components on both stock and bond market as an increase in policy rate causes decline in stocks prices and bonds yields. The findings of this study will help the potential investors in making long-term (in general and short-term (in particular investment strategies concerning monetary policy.DOI: 10.15408/sjie.v7i2.7099

  11. A Predictive Likelihood Approach to Bayesian Averaging

    Directory of Open Access Journals (Sweden)

    Tomáš Jeřábek

    2015-01-01

    Full Text Available Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of almost all macroeconomic analysis. In this paper we combine multivariate density forecasts of GDP growth, inflation and real interest rates from four various models, two type of Bayesian vector autoregression (BVAR models, a New Keynesian dynamic stochastic general equilibrium (DSGE model of small open economy and DSGE-VAR model. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. Because forecast accuracy of observed models are different, the weighting scheme based on the predictive likelihood, the trace of past MSE matrix, model ranks are used to combine the models. The equal-weight scheme is used as a simple combination scheme. The results show that optimally combined densities are comparable to the best individual models.

  12. The Asymmetric Effects of Oil Price Changes on the Economic Activities in Indonesia

    Directory of Open Access Journals (Sweden)

    Rina Juliet Artami

    2018-01-01

    Full Text Available This paper analyzes the asymmetric impact of oil price changes on the economic growth of and inflation in Indonesia by using the vector autoregression (VAR model for the period from 1990Q1 to 2016Q4. The results show that the impact of oil price changes on the gross domestic product (GDP is asymmetric, as a drop in oil prices decreases the GDP, whereas an increase in oil prices does not significantly affect GDP. It is crucial for Indonesia to reduce its dependency on oil, mainly as its primary source of revenue, and also consider utilizing more sources of renewable energy. At the same time, the effects of both the positive and negative changes in oil prices are found to be not statistically significant to inflation. The lack of impact of oil price changes on inflation can explain by the implementation of the fuel price subsidy in Indonesia.DOI: 10.15408/sjie.v7i1.6052

  13. INVESTIGATING FINANCIAL INNOVATION AND EUROPEAN CAPITAL MARKETS. THE CASE OF CATASTROPHE BONDS AND LISTED REINSURANCE COMPANIES

    Directory of Open Access Journals (Sweden)

    CONSTANTIN LAURA-GABRIELA

    2014-12-01

    Full Text Available Focusing on the financial innovation – stock market interconnections, the present research studies the association between the insurance-linked market activity of European (reinsurance companies and their evolution on the capital markets. With the aim of emphasizing the connections from the perspective of the stock performance and their risk, the empirical analysis is based on vector autoregression (VAR and Granger causality analyses. The proposed examination is further developed by considering both impulse response functions and variance decomposition insights. The proxies of the catastrophe bond market, as financial innovation, there are employed both the size and the number of catastrophe bonds transactions, while the stock returns and their standard deviation stand for representatives of the evolution of the reinsurance companies on the capital markets in terms of financial performance and risk. The main results confirm other studies, suggesting that the effects of issuing cat bonds on the ceding companies is reflected rather in terms of stocks’ risk diminishing

  14. INVESTIGATING FINANCIAL INNOVATION AND EUROPEAN CAPITAL MARKETS. THE CASE OF CATASTROPHE BONDS AND LISTED REINSURANCE COMPANIES

    Directory of Open Access Journals (Sweden)

    CONSTANTIN LAURA-GABRIELA

    2014-12-01

    Full Text Available Focusing on the financial innovation – stock market interconnections, the present research studies the association between the insurance-linked market activity of European (reinsurance companies and their evolution on the capital markets. With the aim of emphasizing the connections from the perspective of the stock performance and their risk, the empirical analysis is based on vector autoregression (VAR and Granger causality analyses. The proposed examination is further developed by considering both impulse response functions and variance decomposition insights. The proxies of the catastrophe bond market, as financial innovation, there are employed both the size and the number of catastrophe bonds transactions, while the stock returns and their standard deviation stand for representatives of the evolution of the reinsurance companies on the capital markets in terms of financial performance and risk. The main results confirm other studies, suggesting that the effects of issuing cat bonds on the ceding companies is reflected rather in terms of stocks’ risk diminishing.

  15. Coal Price Forecasting and Structural Analysis in China

    Directory of Open Access Journals (Sweden)

    Xiaopeng Guo

    2016-01-01

    Full Text Available Coal plays an important role in China’s energy structure and its price has been continuously decreasing since the second half of 2012. Constant low price of coal affected the profits of coal enterprises and the coal use of its downstream firms; the precision of coal price provides a reference for these enterprises making their management strategy. Based on the historical data of coal price and related factors such as port stocks, sales volume, futures prices, Producer Price Index (PPI, and crude oil price rate from November 2013 to June 2016, this study aims to forecast coal price using vector autoregression (VAR model and portray the dynamic correlations between coal price and variables by the impulse response function and variance decomposition. Comparing predicted and actual values, the root mean square error (RMSE was small which indicated good precision of this model. Thus this short period prediction can help these enterprises make the right business decisions.

  16. The macroeconomic effects of oil price fluctuations on a small open oil-producing country. The case of Trinidad and Tobago

    International Nuclear Information System (INIS)

    Lorde, Troy; Thomas, Chrystol; Jackman, Mahalia

    2009-01-01

    Using vector autoregressive (VAR) methodology, this paper empirically investigates the macroeconomic effects of oil price fluctuations on Trinidad and Tobago. Overall, we find that the price of oil is a major determinant of economic activity of the country. Our impulse response functions suggest that following a positive oil price shock, output falls within the first two years followed by positive and growing response. We also investigate the macroeconomic impact of oil price volatility. Results suggest that an unanticipated shock to oil price volatility brings about random swings in the macroeconomy; however, only government revenue and the price level exhibit significant responses. With regard to the magnitude of the responses, shocks to oil price volatility tend to yield smaller macroeconomic impacts in comparison to shocks to oil prices. Variance decompositions suggest that the price of oil is a major component of forecast variation for most macroeconomic variables. Finally, Granger-causality tests indicate causality from oil prices to output and oil prices to government revenue. (author)

  17. THE INFLATION IMPACT OF SELECTED EUROPEAN UNION MEMBERS ON POLISH INFLATION

    Directory of Open Access Journals (Sweden)

    Jarosław Czaja

    2012-06-01

    Full Text Available The article aims at determining the inflation influence between Poland and selected EU member states. Although for some time the general inflation level in those countries was definitely controllable, the problem seems to be returning. That is why in this article, using the model of Vector AutoRegression (VAR and Granger causality test, we are attempting to determine inflation influences on Poland. The study confirmed the impact of the selected countries on Polish inflation, expressed the general HICP index. However, in the case of Germany, the method has not proved the existence of such interactions. For this reason, it is made an attempt to clarify the reasons for non-compliance findings with data showing Germany as a Polish main trading partner for more than two decades. The authors try to show that lack of influence can be seen in the excessive generality of the main HICP index and predict that the chosen method confirm the effect of foreign trade indices in the HICP.

  18. Transmission of Shock across International Stock Markets: An Econometric Analysis

    Directory of Open Access Journals (Sweden)

    Shalini TALWAR

    2018-05-01

    Full Text Available The risk of spillover of volatility among international stock markets has increased manifold and it needs to be diagnosed comprehensively. In this paper, the authors have used 11 stock indices to identify influential markets and detect the direction of transmission of shock across markets in different time zones using Granger causality test, Johansen cointegration test and vector autoregression. The findings of VAR show that the forecast error at the 10-day horizon explained by their own innovation is highest for the Australian and Chinese markets followed by Japan, India, Brazil and Russia.Markets of Germany, UK, USA and Canada are influenced by the Australian market. In fact, the Australian market is seen to be the most influential market among the markets under the study. The impact of Chinese and Canadian markets is found to be the least. These results can be useful for optimal option valuation, effective portfolio allocation and performance benchmarking

  19. A molecular epidemiological study of var gene diversity to characterize the reservoir of Plasmodium falciparum in humans in Africa.

    Directory of Open Access Journals (Sweden)

    Donald S Chen

    2011-02-01

    Full Text Available The reservoir of Plasmodium infection in humans has traditionally been defined by blood slide positivity. This study was designed to characterize the local reservoir of infection in relation to the diverse var genes that encode the major surface antigen of Plasmodium falciparum blood stages and underlie the parasite's ability to establish chronic infection and transmit from human to mosquito.We investigated the molecular epidemiology of the var multigene family at local sites in Gabon, Senegal and Kenya which differ in parasite prevalence and transmission intensity. 1839 distinct var gene types were defined by sequencing DBLα domains in the three sites. Only 76 (4.1% var types were found in more than one population indicating spatial heterogeneity in var types across the African continent. The majority of var types appeared only once in the population sample. Non-parametric statistical estimators predict in each population at minimum five to seven thousand distinct var types. Similar diversity of var types was seen in sites with different parasite prevalences.Var population genomics provides new insights into the epidemiology of P. falciparum in Africa where malaria has never been conquered. In particular, we have described the extensive reservoir of infection in local African sites and discovered a unique var population structure that can facilitate superinfection through minimal overlap in var repertoires among parasite genomes. Our findings show that var typing as a molecular surveillance system defines the extent of genetic complexity in the reservoir of infection to complement measures of malaria prevalence. The observed small scale spatial diversity of var genes suggests that var genetics could greatly inform current malaria mapping approaches and predict complex malaria population dynamics due to the import of var types to areas where no widespread pre-existing immunity in the population exists.

  20. A Molecular Epidemiological Study of var Gene Diversity to Characterize the Reservoir of Plasmodium falciparum in Humans in Africa

    Science.gov (United States)

    Leliwa-Sytek, Aleksandra; Smith, Terry-Ann; Peterson, Ingrid; Brown, Stuart M.; Migot-Nabias, Florence; Deloron, Philippe; Kortok, Moses M.; Marsh, Kevin; Daily, Johanna P.; Ndiaye, Daouda; Sarr, Ousmane; Mboup, Souleymane; Day, Karen P.

    2011-01-01

    Background The reservoir of Plasmodium infection in humans has traditionally been defined by blood slide positivity. This study was designed to characterize the local reservoir of infection in relation to the diverse var genes that encode the major surface antigen of Plasmodium falciparum blood stages and underlie the parasite's ability to establish chronic infection and transmit from human to mosquito. Methodology/Principal Findings We investigated the molecular epidemiology of the var multigene family at local sites in Gabon, Senegal and Kenya which differ in parasite prevalence and transmission intensity. 1839 distinct var gene types were defined by sequencing DBLα domains in the three sites. Only 76 (4.1%) var types were found in more than one population indicating spatial heterogeneity in var types across the African continent. The majority of var types appeared only once in the population sample. Non-parametric statistical estimators predict in each population at minimum five to seven thousand distinct var types. Similar diversity of var types was seen in sites with different parasite prevalences. Conclusions/Significance Var population genomics provides new insights into the epidemiology of P. falciparum in Africa where malaria has never been conquered. In particular, we have described the extensive reservoir of infection in local African sites and discovered a unique var population structure that can facilitate superinfection through minimal overlap in var repertoires among parasite genomes. Our findings show that var typing as a molecular surveillance system defines the extent of genetic complexity in the reservoir of infection to complement measures of malaria prevalence. The observed small scale spatial diversity of var genes suggests that var genetics could greatly inform current malaria mapping approaches and predict complex malaria population dynamics due to the import of var types to areas where no widespread pre-existing immunity in the population

  1. Feasibility of Stochastic Voltage/VAr Optimization Considering Renewable Energy Resources for Smart Grid

    Science.gov (United States)

    Momoh, James A.; Salkuti, Surender Reddy

    2016-06-01

    This paper proposes a stochastic optimization technique for solving the Voltage/VAr control problem including the load demand and Renewable Energy Resources (RERs) variation. The RERs often take along some inputs like stochastic behavior. One of the important challenges i. e., Voltage/VAr control is a prime source for handling power system complexity and reliability, hence it is the fundamental requirement for all the utility companies. There is a need for the robust and efficient Voltage/VAr optimization technique to meet the peak demand and reduction of system losses. The voltages beyond the limit may damage costly sub-station devices and equipments at consumer end as well. Especially, the RERs introduces more disturbances and some of the RERs are not even capable enough to meet the VAr demand. Therefore, there is a strong need for the Voltage/VAr control in RERs environment. This paper aims at the development of optimal scheme for Voltage/VAr control involving RERs. In this paper, Latin Hypercube Sampling (LHS) method is used to cover full range of variables by maximally satisfying the marginal distribution. Here, backward scenario reduction technique is used to reduce the number of scenarios effectively and maximally retain the fitting accuracy of samples. The developed optimization scheme is tested on IEEE 24 bus Reliability Test System (RTS) considering the load demand and RERs variation.

  2. The Burr X Pareto Distribution: Properties, Applications and VaR Estimation

    Directory of Open Access Journals (Sweden)

    Mustafa Ç. Korkmaz

    2017-12-01

    Full Text Available In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate Value-at-Risk (VaR by means of the proposed distribution. We compare the distribution with a few other models to show its versatility in modelling data with heavy tails. VaR estimation with the Burr X Pareto distribution is presented using time series data, and the new model could be considered as an alternative VaR model against the generalized Pareto model for financial institutions.

  3. Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

    Science.gov (United States)

    Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

    2010-12-01

    The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

  4. Testing popular VaR models in EU new member and candidate states

    Directory of Open Access Journals (Sweden)

    Saša Žiković

    2007-12-01

    Full Text Available The impact of allowing banks to calculate their capital requirement based on their internal VaR models, and the impact of regulation changes on banks in transitional countries has not been well studied. This paper examines whether VaR models that are created and suited for developed markets apply to the volatile stock markets of EU new member and candidate states (Bulgaria, Romania, Croatia and Turkey. Nine popular VaR models are tested on five stock indexes from EU new member and candidate states. Backtesting results show that VaR models commonly used in developed stock markets are not well suited for measuring market risk in these markets. Presented findings bear very important implications that have to be addressed by regulators and risk practitioners operating in EU new member andcandidate states. Risk managers have to start thinking outside the frames set by their parent companies or else investors present in these markets may find themselves in serious trouble, dealing with losses that they have not been expecting. National regulators have to take into consideration that simplistic VaR models that are widely used in some developed countries are not well suited for these illiquid and developing stock markets.

  5. Comparison of the specificity of antibodies to VAR2CSA in Cameroonian multigravidae with and without placental malaria

    DEFF Research Database (Denmark)

    Babakhanyan, Anna; Fang, Rui; Wey, Andrew

    2015-01-01

    BACKGROUND: Antibodies (Ab) to VAR2CSA prevent Plasmodium falciparum-infected erythrocytes from sequestrating in the placenta, i.e., prevent placental malaria (PM). The specificity of Ab to VAR2CSA associated with absence of PM is unknown. Accordingly, differences in the specificity of Ab to VAR2......CSA were compared between multigravidae with and without PM who had Ab to VAR2CSA. METHODS: In a retrospective case-control study, plasma collected from Cameroonian multigravidae with (n = 96) and without (n = 324) PM were screened in 21 assays that measured antibody levels to full length VAR2CSA (FV2......), individual VAR2CSA DBL domains, VAR2CSA domains from different genetic backgrounds (variants), as well as proportion of high avidity Ab to FV2. RESULTS: Multigravidae with and without PM had similar levels of Ab to FV2, the six VAR2CSA DBL domains and different variants, while the proportion of high avidity...

  6. Cloning of the Repertoire of Individual Plasmodium falciparum var Genes Using Transformation Associated Recombination (TAR)

    Science.gov (United States)

    Schmid, Christoph D.; Bühlmann, Tobias; Louis, Edward J.; Beck, Hans-Peter

    2011-01-01

    One of the major virulence factors of the malaria causing parasite is the Plasmodium falciparum encoded erythrocyte membrane protein 1 (PfEMP1). It is translocated to It the membrane of infected erythrocytes and expressed from approximately 60 var genes in a mutually exclusive manner. Switching of var genes allows the parasite to alter functional and antigenic properties of infected erythrocytes, to escape the immune defense and to establish chronic infections. We have developed an efficient method for isolating VAR genes from telomeric and other genome locations by adapting transformation-associated recombination (TAR) cloning, which can then be analyzed and sequenced. For this purpose, three plasmids each containing a homologous sequence representing the upstream regions of the group A, B, and C var genes and a sequence homologous to the conserved acidic terminal segment (ATS) of var genes were generated. Co-transfection with P. falciparum strain ITG2F6 genomic DNA in yeast cells yielded 200 TAR clones. The relative frequencies of clones from each group were not biased. Clones were screened by PCR, as well as Southern blotting, which revealed clones missed by PCR due to sequence mismatches with the primers. Selected clones were transformed into E. coli and further analyzed by RFLP and end sequencing. Physical analysis of 36 clones revealed 27 distinct types potentially representing 50% of the var gene repertoire. Three clones were selected for sequencing and assembled into single var gene containing contigs. This study demonstrates that it is possible to rapidly obtain the repertoire of var genes from P. falciparum within a single set of cloning experiments. This technique can be applied to individual isolates which will provide a detailed picture of the diversity of var genes in the field. This is a powerful tool to overcome the obstacles with cloning and assembly of multi-gene families by simultaneously cloning each member. PMID:21408186

  7. Complete mitochondrial genome of Xingguo red carp (Cyprinus carpio var. singuonensis) and purse red carp (Cyprinus carpio var. wuyuanensis).

    Science.gov (United States)

    Hu, Guang-Fu; Liu, Xiang-Jiang; Li, Zhong; Liang, Hong-Wei; Hu, Shao-Na; Zou, Gui-Wei

    2016-01-01

    The complete mitochondrial genomes of Xingguo red carp (Cyprinus carpio var. singuonensis) and purse red carp (Cyprinus carpio var. wuyuanensis) were sequenced. Comparison of these two mitochondrial genomes revealed that the mtDNAs of these two common carp varieties were remarkably similar in genome length, gene order and content, and AT content. However, size variation between these two mitochondrial genomes presented here showed 39 site differences in overall length. About 2 site differences were located in rRNAs, 3 in tRNAs, 3 in the control region, 31 in protein-coding genes. Thirty-one variable bases in the protein-coding regions between the two varieties mitochondrial sequences led to three variable amino acids, which were mainly located in the protein ND5 and ND4.

  8. Islamic vs. Conventional Banking Role in Non-Oil Growth: A Causal Analysis in the Case of Bahrain

    Directory of Open Access Journals (Sweden)

    Abdallah Belhadia

    2014-12-01

    Full Text Available This paper aims to investigate the type of relationship between Islamic vs. Conventional banking and non-Oil economic growth in the case of Bahrain by using annual data 1990-2012 retrieved from Islamic banks and financial institutions information (Ibis-Online of the Islamic Bank of Development (IDB, World Bank development indicators (WB, and the Central Bank of Bahrain (CBB annual reports.This study employs the Johansen and Juselius Cointegration test and Vector Error Correction Model (VECM as well as Vector Autoregressive model (VAR to reveal the long run and short-run causality between the dual banking development and non-Oil GDP growth. The VECM results of the conventional banking show that there is long-run bidirectional causality between all the conventional banking selected indicators and the non-Oil GDP. For the Islamic banking VAR model, there is a unidirectional causality from Islamic banking indicators to the non-oil GDP. There is no evidence on the role of non-oil GDP on the Islamic banking development. Impulse response functions in the two models shows that through one standards deviation positive shock in Islamic vs. Conventional Credit provided to private sector, the non-Oil GDP will be much higher in the next five years if we stimulate the Islamic credit provided to private sector than the conventional banks.Moreover, the Islamic credit provided to the private sector appears to be more procyclical than the credit provided by the conventional banks. However, the fluctuations in the conventional credit are sharper than the Islamic banks’ private credit. This study provides the policy makers in Bahrain with the appropriate evidences to design their policies in fostering the non-Oil sector.

  9. Trans-acting GC-rich non-coding RNA at var expression site modulates gene counting in malaria parasite.

    Science.gov (United States)

    Guizetti, Julien; Barcons-Simon, Anna; Scherf, Artur

    2016-11-16

    Monoallelic expression of the var multigene family enables immune evasion of the malaria parasite Plasmodium falciparum in its human host. At a given time only a single member of the 60-member var gene family is expressed at a discrete perinuclear region called the 'var expression site'. However, the mechanism of var gene counting remains ill-defined. We hypothesize that activation factors associating specifically with the expression site play a key role in this process. Here, we investigate the role of a GC-rich non-coding RNA (ncRNA) gene family composed of 15 highly homologous members. GC-rich genes are positioned adjacent to var genes in chromosome-central gene clusters but are absent near subtelomeric var genes. Fluorescence in situ hybridization demonstrates that GC-rich ncRNA localizes to the perinuclear expression site of central and subtelomeric var genes in trans. Importantly, overexpression of distinct GC-rich ncRNA members disrupts the gene counting process at the single cell level and results in activation of a specific subset of var genes in distinct clones. We identify the first trans-acting factor targeted to the elusive perinuclear var expression site and open up new avenues to investigate ncRNA function in antigenic variation of malaria and other protozoan pathogens. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Orientation of the Fiscal Policy in Tunisia: Structural VAR Analysis

    Directory of Open Access Journals (Sweden)

    Wissem Khanfir

    2017-06-01

    Full Text Available The objective of this paper is to indicate the orientation of fiscal policy in Tunisia, using the structural budget balance, during the period 1972-2014. For this purpose, we estimate a structural VAR model consisting of the fiscal deficit to current GDP ratio and the volume of economic activity represented by the real GDP. We estimate bivariate structural VAR in order to decompose fiscal deficit fluctuations into different disturbances.

  11. Generation of antigenic diversity in Plasmodium falciparum by structured rearrangement of Var genes during mitosis.

    Directory of Open Access Journals (Sweden)

    Antoine Claessens

    2014-12-01

    Full Text Available The most polymorphic gene family in P. falciparum is the ∼60 var genes distributed across parasite chromosomes, both in the subtelomeres and in internal regions. They encode hypervariable surface proteins known as P. falciparum erythrocyte membrane protein 1 (PfEMP1 that are critical for pathogenesis and immune evasion in Plasmodium falciparum. How var gene sequence diversity is generated is not currently completely understood. To address this, we constructed large clone trees and performed whole genome sequence analysis to study the generation of novel var gene sequences in asexually replicating parasites. While single nucleotide polymorphisms (SNPs were scattered across the genome, structural variants (deletions, duplications, translocations were focused in and around var genes, with considerable variation in frequency between strains. Analysis of more than 100 recombination events involving var exon 1 revealed that the average nucleotide sequence identity of two recombining exons was only 63% (range: 52.7-72.4% yet the crossovers were error-free and occurred in such a way that the resulting sequence was in frame and domain architecture was preserved. Var exon 1, which encodes the immunologically exposed part of the protein, recombined in up to 0.2% of infected erythrocytes in vitro per life cycle. The high rate of var exon 1 recombination indicates that millions of new antigenic structures could potentially be generated each day in a single infected individual. We propose a model whereby var gene sequence polymorphism is mainly generated during the asexual part of the life cycle.

  12. Reversal of cisplatin resistance in non-small cell lung cancer stem cells by Taxus chinensis var.

    Science.gov (United States)

    Jiang, Y Q; Xu, X P; Guo, Q M; Xu, X C; Liu, Q Y; An, S H; Xu, J L; Su, F; Tai, J B

    2016-09-02

    Drug resistance in cells is a major impedance to successful treatment of lung cancer. Taxus chinensis var. inhibits the growth of tumor cells and promotes the synthesis of interleukins 1 and 2 and tumor necrosis factor, enhancing immune function. In this study, T. chinensis var.-induced cell death was analyzed in lung cancer cells (H460) enriched for stem cell growth in a defined serum-free medium. Taxus-treated stem cells were also analyzed for Rhodamine 123 (Rh-123) expression by flow cytometry, and used as a standard functional indicator of MDR. The molecular basis of T. chinensis var.-mediated drug resistance was established by real-time PCR analysis of ABCC1, ABCB1, and lung resistance-related protein (LRP) mRNA, and western blot analysis of MRP1, MDR1, and LRP. Our results revealed that stem cells treated with higher doses of T. chinensis var. showed significantly lower growth inhibition rates than did H460 cells (P var. and cisplatin was also significantly inhibited (P var. (P var.-treated stem cells showed significant downregulation of the ABCC1, ABCB1, and LRP mRNA and MRP1, MDR1, and LRP (P var.-mediated downregulation of MRP1, MDR1, and LRP might contribute to the reversal of drug resistance in non-small cell lung cancer stem cells.

  13. CAViaR-based forecast for oil price risk

    International Nuclear Information System (INIS)

    Huang, Dashan; Yu, Baimin; Fabozzi, Frank J.; Fukushima, Masao

    2009-01-01

    As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367-381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction. (author)

  14. Metabolomic variation of brassica rapa var. rapa (var. raapstelen) and raphanus sativus l. at different developmental stages

    International Nuclear Information System (INIS)

    Jahangir, M.; Farid, I.B.A.

    2014-01-01

    Brassica rapa (var. raapstelen) and Raphanus sativus (red radish) are being used as food and fodder while also known as model in recent plant research due to the diversity of metabolites as well as genetic resemblance to Arabidopsis. This study explains the change in metabolites (amino acids, organic acids, chlorophyll, carotenoids, tocopherols, ascorbic acid, sucrose, phenylpropanoids and glucosinolates) during plant development. In present study the metabolomic variation in relation to plant growth has been evaluated, for Brassica rapa (var. raapstelen) and red radish (Raphanus sativus) at three different developmental stages. A non-targeted and targeted metabolomic approach by NMR and HPLC in combination with Principal component analysis (PCA) of the data was used to identify phytochemicals being influenced by plant growth. The results lead to the better understanding of metabolic changes during plant development and show the importance of plant age with respect to the metabolomic profile of vegetables. (author)

  15. Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

    Science.gov (United States)

    Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

    2015-04-01

    A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built

  16. Clinical development of a VAR2CSA-based placental malaria vaccine PAMVAC

    DEFF Research Database (Denmark)

    Gbédandé, Komi; Fievet, Nadine; Viwami, Firmine

    2017-01-01

    Background  The antigen VAR2CSA plays a pivotal role in the pathophysiology of pregnancy-associated malaria (PAM) caused by Plasmodium falciparum. A VAR2CSA-based vaccine candidate, PAMVAC, is under development by an EU-funded multi-country consortium (PlacMalVac project). As part of PAMVAC...

  17. In vitro antioxidant and anticancer effects of solvent fractions from Prunella vulgaris var. lilacina.

    Science.gov (United States)

    Hwang, Yu-Jin; Lee, Eun-Ju; Kim, Haeng-Ran; Hwang, Kyung-A

    2013-11-09

    Recently, considerable attention has been focused on exploring the potential antioxidant properties of plant extracts or isolated products of plant origin. Prunella vulgaris var. lilacina is widely distributed in Korea, Japan, China, and Europe, and it continues to be used to treat inflammation, eye pain, headache, and dizziness. However, reports on the antioxidant activities of P. vulgaris var. lilacina are limited, particularly concerning the relationship between its phenolic content and antioxidant capacity. In this study, we investigated the antioxidant and anticancer activities of an ethanol extract from P. vulgaris var. lilacina and its fractions. Dried powder of P. vulgaris var. lilacina was extracted with ethanol, and the extract was fractionated to produce the hexane fraction, butanol fraction, chloroform fraction and residual water fraction. The phenolic content was assayed using the Folin-Ciocalteu colorimetric method. Subsequently, the antioxidant activities of the ethanol extract and its fractions were analyzed employing various antioxidant assay methods including DPPH, FRAP, ABTS, SOD activity and production of reactive oxygen species. Additionally, the extract and fractions were assayed for their ability to exert cytotoxic activities on various cancer cells using the MTT assay. We also investigated the expression of genes associated with apoptotic cell death by RT-PCR. The total phenolic contents of the ethanol extract and water fraction of P. vulgaris var. lilacina were 303.66 and 322.80 mg GAE/g dry weight (or fractions), respectively. The results showed that the ethanol extract and the water fraction of P. vulgaris var. lilacina had higher antioxidant content than other solvent fractions, similar to their total phenolic content. Anticancer activity was also tested using the HepG2, HT29, A549, MKN45 and HeLa cancer cell lines. The results clearly demonstrated that the P. vulgaris var. lilacina ethanol extract induced significant cytotoxic effects

  18. Subcellular distribution and chemical forms of thorium in Brassica juncea var. foliosa

    International Nuclear Information System (INIS)

    Zhou, Sai; Kai, Hailu; Zha, Zhongyong; Fang, Zhendong; Wang, Dingna; Du, Liang; Zhang, Dong; Feng, Xiaojie; Jin, Yongdong; Xia, Chuanqin

    2016-01-01

    Brassica juncea var. foliosa (B. juncea var. foliosa) is a promising species for thorium (Th) phytoextraction due to its large biomass, fast growth rate and high tolerance toward Th. To further understand the mechanisms of Th tolerance, the present study investigated the subcellular distribution and chemical forms of Th found in B. juncea var. foliosa Our results indicated that in both roots and leaves, Th contents in different parts of the cells follow the order of cell wall > membranes and soluble fraction > organelles. In particular, Transmission Electron Microscope (TEM) analysis showed that Th was abundantly located in cell walls of the roots. Additionally, when plants were exposed to different concentrations of Th, we have found that Th existed in B. juncea var. foliosa with different chemical forms. Much of the Th extracted by 2% acetic acid (HAc), 1 M NaCl and HCl in roots with the percentage distribution varied from 47.2% to 62.5%, while in leaves, most of the Th was in the form of residue and the subdominant amount of Th was extracted by HCl, followed by 2% HAc. This suggested that Th compartmentation in cytosol and integration with phosphate or proteins in cell wall might be responsible for the tolerance of B. juncea var. foliosa to the stress of Th. - Highlights: • Brassica juncea var. foliosa can adapt to the stress of Th(<200 μM) under hydroponic condition. • Th was selectively distributed on cell wall, membranes and soluble fraction. • Th mainly existed in low-toxicity forms which were benefit for Th tolerance.

  19. Integer valued autoregressive processes with generalized discrete Mittag-Leffler marginals

    Directory of Open Access Journals (Sweden)

    Kanichukattu K. Jose

    2013-05-01

    Full Text Available In this paper we consider a generalization of discrete Mittag-Leffler distributions. We introduce and study the properties of a new distribution called geometric generalized discrete Mittag-Leffler distribution. Autoregressive processes with geometric generalized discrete Mittag-Leffler distributions are developed and studied. The distributions are further extended to develop a more general class of geometric generalized discrete semi-Mittag-Leffler distributions. The processes are extended to higher orders also. An application with respect to an empirical data on customer arrivals in a bank counter is also given. Various areas of potential applications like human resource development, insect growth, epidemic modeling, industrial risk modeling, insurance and actuaries, town planning etc are also discussed.

  20. Analysis of nonlinear systems using ARMA [autoregressive moving average] models

    International Nuclear Information System (INIS)

    Hunter, N.F. Jr.

    1990-01-01

    While many vibration systems exhibit primarily linear behavior, a significant percentage of the systems encountered in vibration and model testing are mildly to severely nonlinear. Analysis methods for such nonlinear systems are not yet well developed and the response of such systems is not accurately predicted by linear models. Nonlinear ARMA (autoregressive moving average) models are one method for the analysis and response prediction of nonlinear vibratory systems. In this paper we review the background of linear and nonlinear ARMA models, and illustrate the application of these models to nonlinear vibration systems. We conclude by summarizing the advantages and disadvantages of ARMA models and emphasizing prospects for future development. 14 refs., 11 figs

  1. Least squares estimation in a simple random coefficient autoregressive model

    DEFF Research Database (Denmark)

    Johansen, S; Lange, T

    2013-01-01

    The question we discuss is whether a simple random coefficient autoregressive model with infinite variance can create the long swings, or persistence, which are observed in many macroeconomic variables. The model is defined by yt=stρyt−1+εt,t=1,…,n, where st is an i.i.d. binary variable with p...... we prove the curious result that View the MathML source. The proof applies the notion of a tail index of sums of positive random variables with infinite variance to find the order of magnitude of View the MathML source and View the MathML source and hence the limit of View the MathML source...

  2. Autoregressive techniques for acoustic detection of in-sodium water leaks

    International Nuclear Information System (INIS)

    Hayashi, K.

    1997-01-01

    We have been applied a background signal whitening filter built by univariate autoregressive model to the estimation problem of the leak start time and duration. In the 1995 present benchmark stage, we evaluated the method using acoustic signals from real hydrogen or water/steam injection experiments. The results show that the signal processing technique using this filter can detect reliability the leak signals with a sufficient signal-to-noise ratio. Even if the sensor signal contains non-boiling or non-leak high-amplitude pulses, they can be classified by spectral information. Especially, the feature signal made from the time-frequency spectrum of the filtered signal is very sensitive and useful. (author). 8 refs, 14 figs, 6 tabs

  3. Vector Nonlinear Time-Series Analysis of Gamma-Ray Burst Datasets on Heterogeneous Clusters

    Directory of Open Access Journals (Sweden)

    Ioana Banicescu

    2005-01-01

    Full Text Available The simultaneous analysis of a number of related datasets using a single statistical model is an important problem in statistical computing. A parameterized statistical model is to be fitted on multiple datasets and tested for goodness of fit within a fixed analytical framework. Definitive conclusions are hopefully achieved by analyzing the datasets together. This paper proposes a strategy for the efficient execution of this type of analysis on heterogeneous clusters. Based on partitioning processors into groups for efficient communications and a dynamic loop scheduling approach for load balancing, the strategy addresses the variability of the computational loads of the datasets, as well as the unpredictable irregularities of the cluster environment. Results from preliminary tests of using this strategy to fit gamma-ray burst time profiles with vector functional coefficient autoregressive models on 64 processors of a general purpose Linux cluster demonstrate the effectiveness of the strategy.

  4. Silence, Metaperformance, and Communication in Pedro Almodóvar's "Hable con ella"

    Science.gov (United States)

    Fellie, Maria C.

    2016-01-01

    Many scenes in Pedro Almodóvar's "Hable con ella" (2002) include shots of metaperformances such as silent films, dances, television shows, concerts, and bullfights. Spectators often observe passive characters who are in turn observing. By presenting these performances within cinematic performance, Almodóvar highlights our role as viewers…

  5. The Influence of Sub-Unit Composition and Expression System on the Functional Antibody Response in the Development of a VAR2CSA Based Plasmodium falciparum Placental Malaria Vaccine

    DEFF Research Database (Denmark)

    Nielsen, Morten A; dos Santos Marques Resende, Mafalda; de Jongh, Willem A

    2015-01-01

    -functional antibodies, and furthermore influence the folding, stability and yield of expression. Candidate antigens from the pre-clinical development expressed in High-Five insect cells using the baculovirus expression vector system were transitioned into the Drosophila Schneider-2 cell (S2) expression-system compliant...... with clinical development. The functional capacity of antibodies against antigens expressed in High-Five cells or in S2 cells was equivalent. This enabled an extensive down-selection of S2 insect cell-expressed antigens primarily encompassing the minimal CSA-binding region of VAR2CSA. In general, we found...

  6. Chemopreventive and Anticancer Activities of Allium victorialis var. platyphyllum Extracts.

    Science.gov (United States)

    Kim, Hyun-Jeong; Park, Min Jeong; Park, Hee-Juhn; Chung, Won-Yoon; Kim, Ki-Rim; Park, Kwang-Kyun

    2014-09-01

    Allium victorialis var. platyphyllum is an edible perennial herb and has been used as a vegetable or as a Korean traditional medicine. Allium species have received much attention owing to their diverse pharmacological properties, including antioxidative, anti-inflammatory, and anticancer activities. However, A. victorialis var. platyphyllum needs more study. The chemopreventive potential of A. victorialis var. platyphyllum methanol extracts was examined by measuring 12-O-tetra-decanoylphorbol 13-acetate (TPA)-induced superoxide anion production in the differentiated HL-60 cells, TPA-induced mouse ear edema, and Ames/Salmonella mutagenicity. The apoptosis-inducing capabilities of the extracts were evaluated by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay, 4',6-diamidino-2-phenylindole staining, and the DNA fragmentation assay in human colon cancer HT-29 cells. Antimetastatic activities of the extracts were also investigated in an experimental mouse lung metastasis model. The methanol extracts of A. victorialis var. platyphyllum rhizome (AVP-R) and A. victorialis var. platyphyllum stem (AVP-S) dose-dependently inhibited the TPA-induced generation of superoxide anion in HL-60 cells and TPA-induced ear edema in mice, as well as 7,12-dimethylbenz[a]anthracene (DMBA) and tert-butyl hydroperoxide (t-BOOH) -induced bacterial mutagenesis. AVP-R and AVP-S reduced cell viability in a dose-related manner and induced apoptotic morphological changes and internucleosomal DNA fragmentation in HT-29 cells. In the experimental mouse lung metastasis model, the formation of tumor nodules in lung tissue was significantly inhibited by the treatment of the extracts. AVP-R and AVP-S possess antioxidative, anti-inflammatory, antimutagenic, proapoptotic, and antimetastatic activities. Therefore, these extracts can serve as a beneficial supplement for the prevention and treatment of cancer.

  7. Amanitin and phallotoxin concentration in Amanita phalloides var. alba mushroom.

    Science.gov (United States)

    Kaya, Ertugrul; Yilmaz, Ismail; Sinirlioglu, Zeynep Aydin; Karahan, Selim; Bayram, Recep; Yaykasli, Kursat Oguz; Colakoglu, Serdar; Saritas, Ayhan; Severoglu, Zeki

    2013-12-15

    Although rarely seen, Amanita phalloides var. alba, a variety of A. phalloides type mushrooms, causes mushroom poisoning resulting in death. Since it is frequently confused with some edible mushrooms due to its white colored cap and macroscopic appearance, it becomes important in toxicological terms. Knowledge of the toxin amount contained in this mushroom type is invaluable in the treatment of cases involving poisoning. In this study, we examined the toxin levels of various parts of the A. phalloides var. alba mushroom growing Duzce region of Turkey. Toxin analyses were carried out for A. phalloides var. alba, which were collected from the forests Duzce region of Turkey in 2011, as a whole and also separately in its spore, pileus, gills, stipe and volva parts. The alpha amanitin, beta amanitin, gamma amanitin, phalloidin and phallacidine analyses of the mushrooms were carried out using the RP-HPLC method. A genetic analysis of the mushroom showed that it had similar genetic characteristics as A. phalloides and was a variety of it. The lowest toxins quantity was detected in spores, volva and stipe among all parts of the mushroom. The maximum amount of amatoxins was measured in the gills. The pileus also contained a high amount of amatoxins. Generally, amatoxins and phallotoxin concentrations were lower as compared to A. phalloides, but interestingly all toxins other than gamma toxin were higher in the spores of A. phalloides var. alba. The amount of toxin in all of its parts had sufficient concentrations to cause death. With this study, the amatoxin and phallotoxin concentrations in A. phalloides var. alba mushroom and in its parts have been revealed in detail for the first time. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Subcellular distribution and chemical forms of thorium in Brassica juncea var. foliosa.

    Science.gov (United States)

    Zhou, Sai; Kai, Hailu; Zha, Zhongyong; Fang, Zhendong; Wang, Dingna; Du, Liang; Zhang, Dong; Feng, Xiaojie; Jin, Yongdong; Xia, Chuanqin

    2016-06-01

    Brassica juncea var. foliosa (B. juncea var. foliosa) is a promising species for thorium (Th) phytoextraction due to its large biomass, fast growth rate and high tolerance toward Th. To further understand the mechanisms of Th tolerance, the present study investigated the subcellular distribution and chemical forms of Th found in B. juncea var. foliosa Our results indicated that in both roots and leaves, Th contents in different parts of the cells follow the order of cell wall > membranes and soluble fraction > organelles. In particular, Transmission Electron Microscope (TEM) analysis showed that Th was abundantly located in cell walls of the roots. Additionally, when plants were exposed to different concentrations of Th, we have found that Th existed in B. juncea var. foliosa with different chemical forms. Much of the Th extracted by 2% acetic acid (HAc), 1 M NaCl and HCl in roots with the percentage distribution varied from 47.2% to 62.5%, while in leaves, most of the Th was in the form of residue and the subdominant amount of Th was extracted by HCl, followed by 2% HAc. This suggested that Th compartmentation in cytosol and integration with phosphate or proteins in cell wall might be responsible for the tolerance of B. juncea var. foliosa to the stress of Th. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Nonlinear structural damage detection using support vector machines

    Science.gov (United States)

    Xiao, Li; Qu, Wenzhong

    2012-04-01

    An actual structure including connections and interfaces may exist nonlinear. Because of many complicated problems about nonlinear structural health monitoring (SHM), relatively little progress have been made in this aspect. Statistical pattern recognition techniques have been demonstrated to be competitive with other methods when applied to real engineering datasets. When a structure existing 'breathing' cracks that open and close under operational loading may cause a linear structural system to respond to its operational and environmental loads in a nonlinear manner nonlinear. In this paper, a vibration-based structural health monitoring when the structure exists cracks is investigated with autoregressive support vector machine (AR-SVM). Vibration experiments are carried out with a model frame. Time-series data in different cases such as: initial linear structure; linear structure with mass changed; nonlinear structure; nonlinear structure with mass changed are acquired.AR model of acceleration time-series is established, and different kernel function types and corresponding parameters are chosen and compared, which can more accurate, more effectively locate the damage. Different cases damaged states and different damage positions have been recognized successfully. AR-SVM method for the insufficient training samples is proved to be practical and efficient on structure nonlinear damage detection.

  10. Taxonomic study on Japanese Salvia (Lamiaceae): Phylogenetic position of S. akiensis, and polyphyletic nature of S. lutescens var. intermedia.

    Science.gov (United States)

    Takano, Atsuko

    2017-01-01

    Both Salvia akiensis and S. lutescens (Lamiaceae) are endemic to Japan. Salvia akiensis was recently described in 2014 in the Chugoku (= SW Honshu) region, and each four varieties of S. lutescens distributed allopatrically. Among varieties in S. lutescens , var. intermedia show a disjunctive distribution in the Kanto (=E Honshu) and Kinki (= W Honshu) regions. Recent field studies of S. lutescens var. intermedia revealed several morphological differences between the Kanto and Kinki populations. Here, I evaluated these differences among Salvia lutescens var. intermedia and its allies with morphological analysis and molecular phylogenetic analyses of nuclear ribosomal DNA (internal and external transcribed spacer regions) and plastid DNA ( ycf1-rps15 spacer, rbcL , and trnL-F ) sequences. Both morphological analysis and molecular phylogenetic analyses showed that S. lutescens var. intermedia from the Kinki region and var. lutescens were closely related to each other. However, var. intermedia from the Kanto region exhibited an association with S. lutescens var. crenata and var. stolonifera, which also grew in eastern Japan, rather than var. intermedia in the Kinki region. These results indicated that S. lutescens var. intermedia is not a taxon with a disjunctive distribution, but a combination of two or more allopatric taxa. Present study also suggested that S. akiensis was most closely related to S. omerocalyx .

  11. SCoT: a Python toolbox for EEG source connectivity.

    Science.gov (United States)

    Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R

    2014-01-01

    Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.

  12. Metabolomic variation of brassica rapa var. rapa (var. raapstelen) and raphanus sativus l. at different developmental stages

    NARCIS (Netherlands)

    Jahangir, M.; Abdel-Farid, I.B.; Vos, de C.H.R.; Jonker, H.H.; Choi, Y.H.; Verpoorte, R.

    2014-01-01

    Brassica rapa (var. raapstelen) and Raphanus sativus (red radish) are being used as food and fodder while also known as model in recent plant research due to the diversity of metabolites as well as genetic resemblance to Arabidopsis. This study explains the change in metabolites (amino acids,

  13. A Novel Virus-Like Particle Based Vaccine Platform Displaying the Placental Malaria Antigen VAR2CSA.

    Directory of Open Access Journals (Sweden)

    Susan Thrane

    Full Text Available Placental malaria caused by Plasmodium falciparum is a major cause of mortality and severe morbidity. Clinical testing of a soluble protein-based vaccine containing the parasite ligand, VAR2CSA, has been initiated. VAR2CSA binds to the human receptor chondroitin sulphate A (CSA and is responsible for sequestration of Plasmodium falciparum infected erythrocytes in the placenta. It is imperative that a vaccine against malaria in pregnancy, if administered to women before they become pregnant, can induce a strong and long lasting immune response. While most soluble protein-based vaccines have failed during clinical testing, virus-like particle (VLP based vaccines (e.g., the licensed human papillomavirus vaccines have demonstrated high efficacy, suggesting that the spatial assembly of the vaccine antigen is a critical parameter for inducing an optimal long-lasting protective immune response. We have developed a VLP vaccine display platform by identifying regions of the HPV16 L1 coat protein where a biotin acceptor site (AviTagTM can be inserted without compromising VLP-assembly. Subsequent biotinylation of Avi-L1 VLPs allow us to anchor monovalent streptavidin (mSA-fused proteins to the biotin, thereby obtaining a dense and repetitive VLP-display of the vaccine antigen. The mSA-VAR2CSA antigen was delivered on the Avi-L1 VLP platform and tested in C57BL/6 mice in comparison to two soluble protein-based vaccines consisting of naked VAR2CSA and mSA-VAR2CSA. The mSA-VAR2CSA Avi-L1 VLP and soluble mSA-VAR2CSA vaccines induced higher antibody titers than the soluble naked VAR2CSA vaccine after three immunizations. The VAR2CSA Avi-L1 VLP vaccine induced statistically significantly higher endpoint titres compared to the soluble mSA-VAR2CSA vaccine, after 1st and 2nd immunization; however, this difference was not statistically significant after 3rd immunization. Importantly, the VLP-VAR2CSA induced antibodies were functional in inhibiting the binding of

  14. Parasitosis intestinales en vendedores ambulantes de comida en Ciudad Bolívar, estado Bolívar, Venezuela | Intestinal parasitosis in food handlers from ciudad Bolívar, Bolívar state, Venezuela

    Directory of Open Access Journals (Sweden)

    Ixora Requena

    2017-11-01

    Full Text Available A descriptive study was performed to determine the prevalence of intestinal parasites in a sample of apparently healthy individuals who sold food in streets in Los Proceres of Ciudad Bolívar, Bolívar State. Fecal samples were collected from 85 individuals, which were analyzed by means of direct examination, qualitative Kato, spontaneous sedimentation and Kinyoun staining. Each individual was filled a clinical epidemiological record and underwent anamnesis and oriented clinical examination. The assessed group comprised 50 women and 35 men with ages 14 to 57 years (mean 15.25 ± 4.21 years. From this group, 50 persons (58.82% were parasitized mainly by Blastocystis spp. (42.22%, Endolimax nana (11.11%, Entamoeba coli (6.67%, Giardia intestinalis (11.11%, Cryptosporidium spp. (11.11% and Cystoisospora belli (4.44%. There was no preference for gender or age (p > 0.05, and persons aged 20 to 25 years were the most affected group. Monoparasitism was observed in 56% (n = 28 cases and 44% (n = 22 of cases had other associated parasites, being the most frequent association between Blastocystis spp with Entamoeba coli and Endolimax nana. It is concluded that there is a high prevalence of intestinal parasitosis among street food handlers.

  15. Evidence for in vitro and in vivo expression of the conserved VAR3 (type 3) plasmodium falciparum erythrocyte membrane protein 1

    DEFF Research Database (Denmark)

    Wang, Christian W; Lavstsen, Thomas; Bengtsson, Dominique C

    2012-01-01

    ABSTRACT: BACKGROUND: Members of the Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) adhesion antigen family are major contributors to the pathogenesis of P. falciparum malaria infections. The PfEMP1-encoding var genes are among the most diverse sequences in nature, but three genes......, var1, var2csa and var3 are found conserved in most parasite genomes. The most severe forms of malaria disease are caused by parasites expressing a subset of antigenically conserved PfEMP1 variants. Thus the ubiquitous and conserved VAR3 PfEMP1 is of particular interest to the research field. Evidence...... of VAR3 expression on the infected erythrocyte surface has never been presented, and var3 genes have been proposed to be transcribed and expressed differently from the rest of the var gene family members. METHODS: In this study, parasites expressing VAR3 PfEMP1 were generated using anti-VAR3 antibodies...

  16. Influence of LAR and VAR on Para-Aminopyridine Antimalarials Targetting Haematin in Chloroquine-Resistance.

    Science.gov (United States)

    Warhurst, David C; Craig, John C; Raheem, K Saki

    2016-01-01

    Antimalarial chloroquine (CQ) prevents haematin detoxication when CQ-base concentrates in the acidic digestive vacuole through protonation of its p-aminopyridine (pAP) basic aromatic nitrogen and sidechain diethyl-N. CQ export through the variant vacuolar membrane export channel, PFCRT, causes CQ-resistance in Plasmodium falciparum but 3-methyl CQ (sontochin SC), des-ethyl amodiaquine (DAQ) and bis 4-aminoquinoline piperaquine (PQ) are still active. This is determined by changes in drug accumulation ratios in parasite lipid (LAR) and in vacuolar water (VAR). Higher LAR may facilitate drug binding to and blocking PFCRT and also aid haematin in lipid to bind drug. LAR for CQ is only 8.3; VAR is 143,482. More hydrophobic SC has LAR 143; VAR remains 68,523. Similarly DAQ with a phenol substituent has LAR of 40.8, with VAR 89,366. In PQ, basicity of each pAP is reduced by distal piperazine N, allowing very high LAR of 973,492, retaining VAR of 104,378. In another bis quinoline, dichlorquinazine (DCQ), also active but clinically unsatisfactory, each pAP retains basicity, being insulated by a 2-carbon chain from a proximal nitrogen of the single linking piperazine. While LAR of 15,488 is still high, the lowest estimate of VAR approaches 4.9 million. DCQ may be expected to be very highly lysosomotropic and therefore potentially hepatotoxic. In 11 pAP antimalarials a quadratic relationship between logLAR and logResistance Index (RI) was confirmed, while log (LAR/VAR) vs logRI for 12 was linear. Both might be used to predict the utility of structural modifications.

  17. BRINE SHRIMP LETHALITY BIOASSAY OF GLAUCIUM GRANDIFLORUM VAR. GRANDIFLORUM

    OpenAIRE

    A. SARI, Ç. ÜNSAL, İ. SARIOĞLU, A. SARI, Ç. ÜNSAL, İ. SARIOĞLU

    2013-01-01

    Türkiye'nin 3 farklı bölgesinden toplanan Glaucium grandiflorum Boiss. et Huet var. grandiflorum örneklerinin toprak üstü kısımlarından elde edilen alkaloit ekstreleri ve bu ekstrelerden elde edilen majör alkaloitler allokriptopin, protopİn, (+)-izokoridin, (+)-korİdin üzerinde brİne shrimp lethality testi yapılarak sitotoksisiteleri İncelenmiştir. Glaucium grandiflorum var. grandiflorum türünün 3 örneği de önemli oranda sitotoksik aktİvite göstermiştir. Allokriptopin, protopin, (+)-izok...

  18. Forecasting Rice Productivity and Production of Odisha, India, Using Autoregressive Integrated Moving Average Models

    Directory of Open Access Journals (Sweden)

    Rahul Tripathi

    2014-01-01

    Full Text Available Forecasting of rice area, production, and productivity of Odisha was made from the historical data of 1950-51 to 2008-09 by using univariate autoregressive integrated moving average (ARIMA models and was compared with the forecasted all Indian data. The autoregressive (p and moving average (q parameters were identified based on the significant spikes in the plots of partial autocorrelation function (PACF and autocorrelation function (ACF of the different time series. ARIMA (2, 1, 0 model was found suitable for all Indian rice productivity and production, whereas ARIMA (1, 1, 1 was best fitted for forecasting of rice productivity and production in Odisha. Prediction was made for the immediate next three years, that is, 2007-08, 2008-09, and 2009-10, using the best fitted ARIMA models based on minimum value of the selection criterion, that is, Akaike information criteria (AIC and Schwarz-Bayesian information criteria (SBC. The performances of models were validated by comparing with percentage deviation from the actual values and mean absolute percent error (MAPE, which was found to be 0.61 and 2.99% for the area under rice in Odisha and India, respectively. Similarly for prediction of rice production and productivity in Odisha and India, the MAPE was found to be less than 6%.

  19. Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

    Science.gov (United States)

    Vazifedan, Turaj; Shitan, Mahendran

    Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

  20. Antioxidant potency of white (Brassica oleracea L. var. capitata) and Chinese (Brassica rapa L. var. pekinensis (Lour.)) cabbage: The influence of development stage, cultivar choice and seed selection

    Czech Academy of Sciences Publication Activity Database

    Šamec, D.; Piljac-Žegarac, J.; Bogovic, M.; Habjanic, K.; Grúz, Jiří

    2011-01-01

    Roč. 128, č. 2 (2011), s. 78-83 ISSN 0304-4238 R&D Projects: GA AV ČR KAN200380801; GA ČR GA301/08/1649 Institutional research plan: CEZ:AV0Z50380511 Keywords : Antimicrobial activity * Antioxidant capacity * Brassica oleracea L. var. capitata * rapa L. var. pekinensis Lour * Cabbage Subject RIV: EF - Botanics Impact factor: 1.527, year: 2011

  1. Influence of beetroot (Beta vulgaris var. cruenta) on mice leukocytes increase

    OpenAIRE

    Amaro, Jony

    2014-01-01

    Background: Beetroot is a flavonoid-containing Mediterranean plant used for food and medicinal purposes. Objectives: To determine the influence of Beta vulgaris var. cruenta extract consumption in increasing albino mice leukocytes. Design: Experimental study. Setting: School N° 1182 bioterium. Biologic material: Twenty male Balb/c albino mice weighing 24 g average. Interventions: Two groups of ten mice each were formed; the experimental group received Beta vulgaris var. cruenta extract at 250...

  2. The Disparate Labor Market Impacts of Monetary Policy

    Science.gov (United States)

    Carpenter, Seth B.; Rodgers, William M., III

    2004-01-01

    Employing two widely used approaches to identify the effects of monetary policy, this paper explores the differential impact of policy on the labor market outcomes of teenagers, minorities, out-of-school youth, and less-skilled individuals. Evidence from recursive vector autoregressions and autoregressive distributed lag models that use…

  3. [Content and distribution of active components in cultivated and wild Taxus chinensis var. mairei plants].

    Science.gov (United States)

    Yu, Shao-Shuai; Sun, Qi-Wu; Zhang, Xiao-Ping; Tian, Sheng-Ni; Bo, Pei-Lei

    2012-10-01

    Taxus chinensis var. mairei is an endemic and endangered plant species in China. The resources of T. chinensis var. mairei have been excessively exploited due to its anti-cancer potential, accordingly, the extant T. chinensis var. mairei population is decreasing. In this paper, ultrasonic extraction and HPLC were adopted to determine the contents of active components paclitaxel, 7-xylosyltaxol and cephalomannine in cultivated and wild T. chinensis var. mairei plants, with the content distribution of these components in different parts of the plants having grown for different years and at different slope aspects investigated. There existed obvious differences in the contents of these active components between cultivated and wild T. chinensis var. mairei plants. The paclitaxel content in the wild plants was about 0.78 times more than that in the cultivated plants, whereas the 7-xylosyltaxol and cephalomannine contents were slishtly higher in the cultivated plants. The differences in the three active components contents between different parts and tree canopies of the plants were notable, being higher in barks and upper tree canopies. Four-year old plants had comparatively higher contents of paclitaxel, 7-xylosyltaxol and cephalomannine (0.08, 0.91 and 0.32 mg x g(-1), respectively), and the plants growing at sunny slope had higher contents of the three active components, with significant differences in the paclitaxel and 7-xylosyltaxol contents and unapparent difference in the cephalomannine content of the plants at shady slope. It was suggested that the accumulation of the three active components in T. chinensis var. mairei plants were closely related to the sunshine conditions. To appropriately increase the sunshine during the artificial cultivation of T. chinensis var. mairei would be beneficial to the accumulation of the three active components in T. chinensis var. mairei plants.

  4. Scleria neesii Kunth var. gadchiroliensis (Cyperaceae, a New Variety from Central India

    Directory of Open Access Journals (Sweden)

    Milind M. Sardesai

    2015-12-01

    Full Text Available A new variety of Scleria P. J. Bergius (Cyperaceae S. neesii Kunth var. gadchiroliensis from Central India is described here with description, line-drawing, photographic illustration and notes. It resembles with S. neesii Kunth var. neesii in overall morphology but differs in having milky white nuts covered with ribbon like hairs on distinct stalk.

  5. Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

    Directory of Open Access Journals (Sweden)

    Sun Zhangzhen

    2012-08-01

    Full Text Available In this paper, an improved weighted least squares (WLS, together with autoregressive (AR model, is proposed to improve prediction accuracy of earth rotation parameters(ERP. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.

  6. Fisher Consistency of AM-Estimates of the Autoregression Parameter Using Hard Rejection Filter Cleaners

    Science.gov (United States)

    1987-02-04

    U5tr,)! P(U 5-t Since U - F with F RS, we get (3.1). Case b: 0 S 5 k -a Now P([U~t]riM) = P(UZk-a) and P([ Ugt ]rM) = P(US-k-a) S P(US-(k-a)) which again...robustness for autoregressive processes." The Annals of Statistics, 12, 843-863. Mallows, C.L. (1980). "Some theory of nonlinear smoothen." The Annals of

  7. Utilizing nanobody technology to target non-immunodominant domains of VAR2CSA.

    Directory of Open Access Journals (Sweden)

    Sisse B Ditlev

    Full Text Available Placental malaria is a major health problem for both pregnant women and their fetuses in malaria endemic regions. It is triggered by the accumulation of Plasmodium falciparum-infected erythrocytes (IE in the intervillous spaces of the placenta and is associated with foetal growth restriction and maternal anemia. IE accumulation is supported by the binding of the parasite-expressed protein VAR2CSA to placental chondroitin sulfate A (CSA. Defining specific CSA-binding epitopes of VAR2CSA, against which to target the immune response, is essential for the development of a vaccine aimed at blocking IE adhesion. However, the development of a VAR2CSA adhesion-blocking vaccine remains challenging due to (i the large size of VAR2CSA and (ii the extensive immune selection for polymorphisms and thereby non-neutralizing B-cell epitopes. Camelid heavy-chain-only antibodies (HcAbs are known to target epitopes that are less immunogenic to classical IgG and, due to their small size and protruding antigen-binding loop, able to reach and recognize cryptic, conformational epitopes which are inaccessible to conventional antibodies. The variable heavy chain (VHH domain is the antigen-binding site of camelid HcAbs, the so called Nanobody, which represents the smallest known (15 kDa intact, native antigen-binding fragment. In this study, we have used the Nanobody technology, an approach new to malaria research, to generate small and functional antibody fragments recognizing unique epitopes broadly distributed on VAR2CSA.

  8. Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

    Science.gov (United States)

    Xie, Pingping; Joyce, Robert; Wu, Shaorong

    2015-04-01

    cloud motion vectors from the GEO/LEO IR based precipitation estimates and the CFS Reanalysis (CFSR) precipitation fields. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the CFSR precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. Error function is experimented to best reflect the performance of the satellite IR based estimates and the CFSR in capturing the movements of precipitating cloud systems over different regions and for different seasons. Quantitative experiments are conducted to optimize the LEO IR based precipitation estimation technique and the 2D-VAR based motion vector analysis system. Detailed results will be reported at the EGU.

  9. Controlling Kuka Industrial Robots : Flexible Communication Interface JOpenShowVar.

    OpenAIRE

    Sanfilippo, Filippo; Hatledal, Lars Ivar; Zhang, Houxiang; Fago, Massimiliano; Pettersen, Kristin Ytterstad

    2015-01-01

    JOpenShowVar is a Java open-source cross-platform communication interface to Kuka industrial robots. This novel interface allows for read-write use of the controlled manipulator variables and data structures. JOpenShowVar, which is compatible with all the Kuka industrial robots that use KUKA Robot Controller version 4 (KR C4) and KUKA Robot Controller version 2 (KR C2), runs as a client on a remote computer connected with the Kuka controller via TCP/IP. Even though only soft real-time applica...

  10. Working alliance inventory applied to virtual and augmented reality (WAI-VAR): psychometrics and therapeutic outcomes.

    Science.gov (United States)

    Miragall, Marta; Baños, Rosa M; Cebolla, Ausiàs; Botella, Cristina

    2015-01-01

    This study examines the psychometric properties of the Working Alliance Inventory-Short (WAI-S) adaptation to Virtual Reality (VR) and Augmented Reality (AR) therapies (WAI-VAR). The relationship between the therapeutic alliance (TA) with VR and AR and clinically significant change (CSC) is also explored. Seventy-five patients took part in this study (74.7% women, M age = 34.41). Fear of flying and adjustment disorder patients received VR therapy, and cockroach phobia patients received AR therapy. Psychometric properties, CSC, one-way ANOVA, Spearman's Correlations and Multiple Regression were calculated. The WAI-VAR showed a unidimensional structure, high internal consistency and adequate convergent validity. "Not changed" patients scored lower on the WAI-VAR than "improved" and "recovered" patients. Correlation between the WAI-VAR and CSC was moderate. The best fitting model for predicting CSC was a linear combination of the TA with therapist (WAI-S) and the TA with VR and AR (WAI-VAR), due to the latter variable slightly increased the percentage of variability accounted for in CSC. The WAI-VAR is the first validated instrument to measure the TA with VR and AR in research and clinical practice. This study reveals the importance of the quality of the TA with technologies in achieving positive outcomes in the therapy.

  11. On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?

    Directory of Open Access Journals (Sweden)

    Ana-Maria Fuertes

    2016-09-01

    Full Text Available This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et al. that constructs the forecast at the market close instead and, accordingly, it models separately the daytime and overnight return processes and their covariance. For a small cap portfolio, the bivariate VaR approach affords superior predictive ability than the ex post overnight VaR approach whereas for a large cap portfolio the results are reversed. The contrast indicates that price discovery at the market open is less efficient for small capitalization, thinly traded stocks.

  12. An Investigation of Feature Models for Music Genre Classification using the Support Vector Classifier

    DEFF Research Database (Denmark)

    Meng, Anders; Shawe-Taylor, John

    2005-01-01

    In music genre classification the decision time is typically of the order of several seconds however most automatic music genre classification systems focus on short time features derived from 10-50ms. This work investigates two models, the multivariate gaussian model and the multivariate...... probability kernel. In order to examine the different methods an 11 genre music setup was utilized. In this setup the Mel Frequency Cepstral Coefficients (MFCC) were used as short time features. The accuracy of the best performing model on this data set was 44% as compared to a human performance of 52...... autoregressive model for modelling short time features. Furthermore, it was investigated how these models can be integrated over a segment of short time features into a kernel such that a support vector machine can be applied. Two kernels with this property were considered, the convolution kernel and product...

  13. Koolipärimuse kogumisest Noarootsis ja Vormsis 2006. aasta kevadel : Rootsi-Eesti lastenaljade kogumik Det var en ko och det var poängen / Piret Voolaid

    Index Scriptorium Estoniae

    Voolaid, Piret, 1971-

    2007-01-01

    Autor käsitleb artiklis Ahvenamaa Põhjamaade Instituudi (Nordens Institut på Åland) eestvedamisel korraldatud lastepärimuse projekti, mille käigus koguti koolipärimust Soomest Ahvenamaalt ja Rootsist Gotlandilt ning Eestist endistelt rannarootsi aladelt. Kogutu põhjal ilmus rootsikeelne antoloogiline naljakogumik Det var en ko och det var poängen. Artiklis keskendutakse välitööde kogumismetoodikale ja tulemustele Eestis. Välitööd toimusid Noarootsi Koolis ja Vormsi Põhikoolis

  14. Penetration, Post-penetration Development, and Reproduction of Meloidogyne incognita on Cucumis melo var. texanus.

    Science.gov (United States)

    Faske, T R

    2013-03-01

    Cucumis melo var. texanus, a wild melon commonly found in the southern United States and two accessions, Burleson Co. and MX 1230, expressed resistance to Meloidogyne incognita in preliminary experiments. To characterize the mechanism of resistance, we evaluated root penetration, post-penetration development, reproduction, and emigration of M. incognita on these two accessions of C. melo var. texanus. Additionally, we evaluated 22 accessions of C. melo var. texanus for their reaction against M. incognita in a greenhouse experiment. Fewer (P ≤ 0.05) J2 penetrated the root system of C. melo var. texanus accessions (Burleson Co. and MX 1230) and C. metuliferus (PI 482452) (resistant control), 7 days after inoculation (DAI) than in C. melo 'Hales Best Jumbo' (susceptible control). A delayed (P ≤ 0.05) rate of nematode development was observed at 7, 14, and 21 DAI that contributed to lower (P ≤ 0.05) egg production on both accessions and C. metuliferus compared with C. melo. Though J2 emigration was observed on all Cucumis genotypes a higher (P ≤ 0.05) rate of J2 emigration was observed from 3 to 6 DAI on accession Burleson Co. and C. metuliferus than on C. melo. The 22 accessions of C. melo var. texanus varied relative to their reaction to M. incognita with eight supporting similar levels of nematode reproduction to that of C. metuliferus. Cucumis melo var. texanus may be a useful source of resistance against root-knot nematode in melon.

  15. Projecting county pulpwood production with historical production and macro-economic variables

    Science.gov (United States)

    Consuelo Brandeis; Dayton M. Lambert

    2014-01-01

    We explored forecasting of county roundwood pulpwood produc-tion with county-vector autoregressive (CVAR) and spatial panelvector autoregressive (SPVAR) methods. The analysis used timberproducts output data for the state of Florida, together with a set ofmacro-economic variables. Overall, we found the SPVAR specifica-tion produced forecasts with lower error rates...

  16. INDUCING RESISTANCE IN COTTON AGAINST COLLETOTRICHUM GOSSYPII VAR. CEPHALOSPORIOIDES WITH ESSENTIAL OILS

    Directory of Open Access Journals (Sweden)

    B. T. Santos

    2016-11-01

    Full Text Available This study aimed to evaluate the potential of essential oils of rosemary (Rosmarinus officinalis, baccharis (Baccharis trimera, lemon grass (Cymbopogon citratus, basil (Ocimum basilicum and eucalyptus (Corymbia citriodora in inducing resistance in cotton plants against C. gossypii var. cephalosporioides. The inductive effect of the essential oils was evaluated in plants growing in pots in the environment, which were treated with 1% essential oil at 47 days of age. 24 hours after elicitor treatment the plants were inoculated with a suspension of 1.5 x 105 conidia mL-1 of C. gossypii var. cephalosporioides. Five evaluations were performed disease and calculated the area under the disease progress curve. All essential oils showed potential for inducing resistance against cotton C. gossypii var. cephalosporioides.

  17. A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory

    DEFF Research Database (Denmark)

    Nonejad, Nima

    We propose a flexible model to describe nonlinearities and long-range dependence in time series dynamics. Our model is an extension of the heterogeneous autoregressive model. Structural breaks occur through mixture distributions in state innovations of linear Gaussian state space models. Monte...... Carlo simulations evaluate the properties of the estimation procedures. Results show that the proposed model is viable and flexible for purposes of forecasting volatility. Model uncertainty is accounted for by employing Bayesian model averaging. Bayesian model averaging provides very competitive...... forecasts compared to any single model specification. It provides further improvements when we average over nonlinear specifications....

  18. Failure and reliability prediction by support vector machines regression of time series data

    International Nuclear Information System (INIS)

    Chagas Moura, Marcio das; Zio, Enrico; Lins, Isis Didier; Droguett, Enrique

    2011-01-01

    Support Vector Machines (SVMs) are kernel-based learning methods, which have been successfully adopted for regression problems. However, their use in reliability applications has not been widely explored. In this paper, a comparative analysis is presented in order to evaluate the SVM effectiveness in forecasting time-to-failure and reliability of engineered components based on time series data. The performance on literature case studies of SVM regression is measured against other advanced learning methods such as the Radial Basis Function, the traditional MultiLayer Perceptron model, Box-Jenkins autoregressive-integrated-moving average and the Infinite Impulse Response Locally Recurrent Neural Networks. The comparison shows that in the analyzed cases, SVM outperforms or is comparable to other techniques. - Highlights: → Realistic modeling of reliability demands complex mathematical formulations. → SVM is proper when the relation input/output is unknown or very costly to be obtained. → Results indicate the potential of SVM for reliability time series prediction. → Reliability estimates support the establishment of adequate maintenance strategies.

  19. Application of superconducting coils to VAR control in electric power systems: a proposal

    International Nuclear Information System (INIS)

    Boenig, H.J.; Hassenzahl, W.V.

    1979-11-01

    During the last eight years, static VAR-control systems with thyristor-controlled, room-temperature reactors have been used in electrical systems for voltage control and system stabilization. In this proposal, we describe a new static VAR-control system that uses an asymmetrically controlled Graetz bridge and a superconducting dc coil. Preliminary studies indicate that the proposed system will have lower overall losses and that its capital cost and electrical characteristics are comparable to those of a conventional system. Three- and four-year programs for developing the electronic circuitry and superconducting coils for VAR control, culminating in the installation and testing of an approx. 40-MVAR system, are proposed

  20. Numerical and structural chromosome aberrations in cauliflower (Brassica oleracea var. botrytis) and Arabidopsis thaliana

    NARCIS (Netherlands)

    Ji, X.

    2014-01-01

    Numerical and structural chromosome aberrations in cauliflower (Brassica oleracea var. botrytis) and Arabidopsis thaliana.

    I studied numerical and structural chromosome aberrations in cauliflower (Brassica oleracea var. botrytis) and