On the Kendall Correlation Coefficient

OpenAIRE

Stepanov, Alexei

2015-01-01

In the present paper, we first discuss the Kendall rank correlation coefficient. In continuous case, we define the Kendall rank correlation coefficient in terms of the concomitants of order statistics, find the expected value of the Kendall rank correlation coefficient and show that the later is free of n. We also prove that in continuous case the Kendall correlation coefficient converges in probability to its expected value. We then propose to consider the expected value of the Kendall rank ...

MODELLING THE EFFECTS OF LAND-USE CHANGES ON CLIMATE: A CASE STUDY ON YAMULA DAM

OpenAIRE

Ü. Köylü; A. Geymen

2016-01-01

Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial’s land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spa...

Non-parametric tests of productive efficiency with errors-in-variables

NARCIS (Netherlands)

Kuosmanen, T.K.; Post, T.; Scholtes, S.

2007-01-01

We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, following the approach of Varian. [1985. Nonparametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30(1/2), 445-458]. The test is based on the general Pareto-Koopmans

Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

Science.gov (United States)

Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

2017-06-30

Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Using exogenous variables in testing for monotonic trends in hydrologic time series

Science.gov (United States)

Alley, William M.

1988-01-01

One approach that has been used in performing a nonparametric test for monotonic trend in a hydrologic time series consists of a two-stage analysis. First, a regression equation is estimated for the variable being tested as a function of an exogenous variable. A nonparametric trend test such as the Kendall test is then performed on the residuals from the equation. By analogy to stagewise regression and through Monte Carlo experiments, it is demonstrated that this approach will tend to underestimate the magnitude of the trend and to result in some loss in power as a result of ignoring the interaction between the exogenous variable and time. An alternative approach, referred to as the adjusted variable Kendall test, is demonstrated to generally have increased statistical power and to provide more reliable estimates of the trend slope. In addition, the utility of including an exogenous variable in a trend test is examined under selected conditions.

Analysis of trends of low flow in river stations in eastern Slovakia

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Martina Zeleňáková

2012-01-01

Full Text Available The availability of using hypothesis test techniques to identify the long-term trends of hydrological time series is investigated in this study. The aim is to analyse trends of low flows at streams in eastern Slovakia, namely Poprad, Hornád, Bodva, Bodrog river basins. The article presents a methodology for prediction of hydrological drought based on statistical testing of low stream flows by non-parametric statistical test. The main objective is to identify low flow trends in the selected 63 river stations in eastern Slovakia. The stations with human impacts are also evaluated. The Mann-Kendall non-parametric test has been used to detect trends in hydrological time series. Statistically significant trends have been determined from the trend lines for the whole territory of eastern Slovakia. The results indicate that the observed changes in Slovakian river basins do not have a clearly defined trend.

The Mann-Whitney U: A Test for Assessing Whether Two Independent Samples Come from the Same Distribution

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Nadim Nachar

2008-03-01

Full Text Available It is often difficult, particularly when conducting research in psychology, to have access to large normally distributed samples. Fortunately, there are statistical tests to compare two independent groups that do not require large normally distributed samples. The Mann-Whitney U is one of these tests. In the following work, a summary of this test is presented. The explanation of the logic underlying this test and its application are presented. Moreover, the forces and weaknesses of the Mann-Whitney U are mentioned. One major limit of the Mann-Whitney U is that the type I error or alpha (? is amplified in a situation of heteroscedasticity.

Non-parametric Tuning of PID Controllers A Modified Relay-Feedback-Test Approach

CERN Document Server

Boiko, Igor

2013-01-01

The relay feedback test (RFT) has become a popular and efficient  tool used in process identification and automatic controller tuning. Non-parametric Tuning of PID Controllers couples new modifications of classical RFT with application-specific optimal tuning rules to form a non-parametric method of test-and-tuning. Test and tuning are coordinated through a set of common parameters so that a PID controller can obtain the desired gain or phase margins in a system exactly, even with unknown process dynamics. The concept of process-specific optimal tuning rules in the nonparametric setup, with corresponding tuning rules for flow, level pressure, and temperature control loops is presented in the text.   Common problems of tuning accuracy based on parametric and non-parametric approaches are addressed. In addition, the text treats the parametric approach to tuning based on the modified RFT approach and the exact model of oscillations in the system under test using the locus of a perturbedrelay system (LPRS) meth...

ANALISIS POTENSI RETRIBUSI PELAYANAN PASAR DI KABUPATEN KENDAL

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Herru Dwi Haryono

2017-06-01

Full Text Available Selama periode 2008-2012, realisasi retribusi pelayanan pasar ini mengalami tren naik turun. Sedangkan dari target yang ditentukan dalam komponen retribusi pelayanan pasar yakni retribusi pasar, retribusi sampah/kebersihan dan retribusi sewa kios rata-rata selalu terealisasi melebihi target. Penelitian ini bertujuan untuk mengetahui potensi retribusi pelayanan pasar di Kabupaten Kendal dan apakah target yang ditentukan sudah berdasarkan potensi yang ada. Data yang digunakan dalam penelitian ini adalah data sekunder. Data sekunder dalam penelitian ini berupa data yang bersumber dari BPS Kabupaten Kendal, DPPKAD    Kabupaten Kendal, Disperindag  Kabupaten  Kendal dan  UPTD Dinas  Pasar Kabupaten  Kendal.  Metode analisis yang digunakan yakni analisis deskriptif yakni menghitung potensi retribusi pelayanan pasar di Kabupaten Kendal dan membandingkan potensi dengan target dan apakah target yang ditentukan sesuai berdasarkan potensi yang ada. Hasil penelitian menunjukkan bahwa (1 potensi retribusi pelayanan pasar di Kabupaten Kendal sebesar Rp.5.130.789.600 pertahun. (2 target retribusi pelayanan pasar di Kabupaten Kendal selalu berada dibawah potensi yang ada, jadi kesimpulannya bahwa mekanisme penentuan target tidak berdasarkan potensi yang ada. Berdasarkan hasil anasilis data tersebut, saran yang dapat disampaikan adalah agar pemerintah daerah ataupun pengelola pasar dapat memanfaatkan secara maksimal potensi yang ada agar realisasi penerimaan retribusi pelayanan pasar dapat ditingkatkan lagi dan hendaknya mengevaluasi mekanisme penetapan target berdasarkan potensi yang ada agar kinerja pemerintah maupun pengelola pasar dapat ditingkatkan lagi yang akan berdampak pada realisasi penerimaan retribusi pelayanan pasar. During the period 2008-2012, the actual levy of service this market has been trending up and down. While the targets specified in the component market services levy market fees, garbage fees / levies hygiene and the average

Testing for constant nonparametric effects in general semiparametric regression models with interactions

KAUST Repository

Wei, Jiawei; Carroll, Raymond J.; Maity, Arnab

2011-01-01

We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work

A Nonparametric Test for Seasonal Unit Roots

OpenAIRE

Kunst, Robert M.

2009-01-01

Abstract: We consider a nonparametric test for the null of seasonal unit roots in quarterly time series that builds on the RUR (records unit root) test by Aparicio, Escribano, and Sipols. We find that the test concept is more promising than a formalization of visual aids such as plots by quarter. In order to cope with the sensitivity of the original RUR test to autocorrelation under its null of a unit root, we suggest an augmentation step by autoregression. We present some evidence on the siz...

On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests

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Aaditya Ramdas

2017-01-01

Full Text Available Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich, with a wide variety of statistics having being designed and analyzed, both for the unidimensional and the multivariate setting. Inthisshortsurvey,wefocusonteststatisticsthatinvolvetheWassersteindistance. Usingan entropic smoothing of the Wasserstein distance, we connect these to very different tests including multivariate methods involving energy statistics and kernel based maximum mean discrepancy and univariate methods like the Kolmogorov–Smirnov test, probability or quantile (PP/QQ plots and receiver operating characteristic or ordinal dominance (ROC/ODC curves. Some observations are implicit in the literature, while others seem to have not been noticed thus far. Given nonparametric two-sample testing’s classical and continued importance, we aim to provide useful connections for theorists and practitioners familiar with one subset of methods but not others.

Caracterização temporal do arsênio nos cursos d'água da bacia hidrográfica do Rio das Velhas, MG, Brasil, ao longo de uma década (1998 - 2007

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Cristiano Christofaro

2009-12-01

Full Text Available Arsenic, a metalloid with wide distribution in nature, can be found in natural environments in the forms of high toxicity. Monitoring conducted in the Basin of the das Velhas River, MG, demonstrates the occurrence of this metal in all sampling stations distributed over the water course and main tributaries. Thus, this study aims to evaluate the time trends of concentration of arsenic in water courses of the basin of das Velhas River, considering the data of twenty-nine monitoring stations from 1998 to 2007. The tests included the verification of seasonality, autocorrelation and temporal trend with the non-parametric tests of Mann-Kendall and Mann-Kendall seasonal. Eight sampling stations showed seasonality, with higher concentrations observed in rainy season. The autocorrelation was virtually nonexistent, which may be associated with low sample found in a monitoring program (three to six months. Only seven monitoring stations showed significant negative trend, indicating a reduction in the concentration of arsenic over the period studied. The results showed that the time trend studies have great relevance for the management of pollution of water resources from tracking data, providing subsidies for preventive and corrective measures differentiated between the stations and sampling periods of the year and also be used in evaluation of the effectiveness of these measures.

Temporal characterization of Arsenic in das Velhas River hydrographic basin waters, MG, Brazil for one decade (1998 - 2007

Directory of Open Access Journals (Sweden)

Mônica Maria Diniz Leão

2009-12-01

Full Text Available Arsenic, a metalloid with wide distribution in nature, can be found in natural environments in the forms of high toxicity. Monitoring conducted in the Basin of the das Velhas River, MG, demonstrates the occurrence of this metal in all sampling stations distributed over the water course and main tributaries. Thus, this study aims to evaluate the time trends of concentration of arsenic in water courses of the basin of das Velhas River, considering the data of twenty-nine monitoring stations from 1998 to 2007. The tests included the verification of seasonality, autocorrelation and temporal trend with the non-parametric tests of Mann-Kendall and Mann-Kendall seasonal. Eight sampling stations showed seasonality, with higher concentrations observed in rainy season. The autocorrelation was virtually nonexistent, which may be associated with low sample found in a monitoring program (three to six months. Only seven monitoring stations showed significant negative trend, indicating a reduction in the concentration of arsenic over the period studied. The results showed that the time trend studies have great relevance for the management of pollution of water resources from tracking data, providing subsidies for preventive and corrective measures differentiated between the stations and sampling periods of the year and also be used in evaluation of the effectiveness of these measures.

Testing for constant nonparametric effects in general semiparametric regression models with interactions

KAUST Repository

Wei, Jiawei

2011-07-01

We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.

Penggunaan Kendal Sebagai Media Penyimpan Panas pada Kolektor Surya Plat Datar

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Mustaqimah Mustaqimah

2016-10-01

  Use of Kendal As a Heat Storage Medium on The Flat Solar  Collector Type  Abstract. Solar collector is a device that serves to collect the incoming solar energy and converted into thermal energy and redirects energy into the fluid. This study aimed to develop and test the performance of solar collector using kendal (beef fat as a heat storage medium. The main parts of flat solar collector is constructed of: frame, cover, insulator, copper pipes and absorber. Preparation of flat plate solar collector that is done by heating until melted beef fat. Then inserted it into the copper pipe. After that, the solar collector is placed in a position with a slope angle 20o orientation. Testing was conducted from 09.00 until 17.30 on a sunny day. Based on the results of the study, the highest total radiation occurs on the first day at 4240.82 (Watt hours / m2. The amount of energy received by the collector is highest on the first day which amounted to 5540.07 kJ. The average temperature in the heat storage medium (Kendal amounted 43.20 oC and generates an average outlet temperature that is equal 45.6 oC. The results of this study indicate that the use of kendal as excellent heat storage medium for solar collector temperature remains stable when solar radiation is not there.

A nonparametric empirical Bayes framework for large-scale multiple testing.

Science.gov (United States)

Martin, Ryan; Tokdar, Surya T

2012-07-01

We propose a flexible and identifiable version of the 2-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the nonnull cases. We use a computationally efficient predictive recursion (PR) marginal likelihood procedure to estimate the model parameters, even the nonparametric mixing distribution. This leads to a nonparametric empirical Bayes testing procedure, which we call PRtest, based on thresholding the estimated local false discovery rates. Simulations and real data examples demonstrate that, compared to existing approaches, PRtest's careful handling of the nonnull density can give a much better fit in the tails of the mixture distribution which, in turn, can lead to more realistic conclusions.

Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data

OpenAIRE

CORNELIS A. LOS

2004-01-01

The efficiency of speculative markets, as represented by Fama's 1970 fair game model, is tested on weekly price index data of six Asian stock markets - Hong Kong, Indonesia, Malaysia, Singapore, Taiwan and Thailand - using Sherry's (1992) non-parametric methods. These scientific testing methods were originally developed to analyze the information processing efficiency of nervous systems. In particular, the stationarity and independence of the price innovations are tested over ten years, from ...

Kruskal-Wallis Test in Multiple Comparisons

OpenAIRE

Parys, Dariusz

2009-01-01

In this paper we show that the Kruskal-Wallis test can be transform to quadratic form among the Mann-Whitney or Kendal τ au concordance measures between pairs of treatments. A multiple comparisons procedure based on patterns of transitive ordering among treatments is implement. We also consider the circularity and non-transitive effects. Statystyka testu Kruskala-Wallisa przedstawiona jest w postaci formy kwadratowej z użyciem statystyki Manna-Whitneya lub miar konkordacji τ au Kendalla. N...

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

Science.gov (United States)

Chen, Zhongsheng; Chen, Yaning; Li, Baofu

2013-02-01

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.

A simple non-parametric goodness-of-fit test for elliptical copulas

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Jaser Miriam

2017-12-01

Full Text Available In this paper, we propose a simple non-parametric goodness-of-fit test for elliptical copulas of any dimension. It is based on the equality of Kendall’s tau and Blomqvist’s beta for all bivariate margins. Nominal level and power of the proposed test are investigated in a Monte Carlo study. An empirical application illustrates our goodness-of-fit test at work.

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin

2017-01-19

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

2017-01-01

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Science.gov (United States)

Ahani, Hossien; Kherad, Mehrzad; Kousari, Mohammad Reza; van Roosmalen, Lieke; Aryanfar, Ramin; Hosseini, Seyyed Mashaallah

2013-05-01

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955-2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann-Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.

Thomas Mann som bibelfortolker

DEFF Research Database (Denmark)

Nielsen, Kirsten

2007-01-01

Artiklen beskæftiger sig med Thomas Manns reception og transformation af den gammeltestamentlige fortælling om Josef og hans brødre. Særlig interesse samler sig om de gudsbilleder, værket indeholder, herunder relationen til Satan. Det karakteristiske ved Manns gudsbillede er, at Gud ikke er tydelig...

USING A DEA MANAGEMENT TOOLTHROUGH A NONPARAMETRIC APPROACH: AN EXAMINATION OF URBAN-RURAL EFFECTS ON THAI SCHOOL EFFICIENCY

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SANGCHAN KANTABUTRA

2009-04-01

Full Text Available This paper examines urban-rural effects on public upper-secondary school efficiency in northern Thailand. In the study, efficiency was measured by a nonparametric technique, data envelopment analysis (DEA. Urban-rural effects were examined through a Mann-Whitney nonparametric statistical test. Results indicate that urban schools appear to have access to and practice different production technologies than rural schools, and rural institutions appear to operate less efficiently than their urban counterparts. In addition, a sensitivity analysis, conducted to ascertain the robustness of the analytical framework, revealed the stability of urban-rural effects on school efficiency. Policy to improve school eff iciency should thus take varying geographical area differences into account, viewing rural and urban schools as different from one another. Moreover, policymakers might consider shifting existing resources from urban schools to rural schools, provided that the increase in overall rural efficiency would be greater than the decrease, if any, in the city. Future research directions are discussed.

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

2018-02-01

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

Trends in Mean Annual Streamflows in Serra da Mantiqueira Environmental Protection Area

OpenAIRE

Mateus Ricardo Nogueira Vilanova

2014-01-01

The aim of this study was to detect trends in the mean annual streamflow in watersheds of Serra da Mantiqueira Environmental Protection Area, an important Brazilian conservation area located between Minas Gerais, São Paulo and Rio de Janeiro States. Historical series of four selected streamgage stations were analyzed for the periods of 1980-1998 and 1980-2009, using the Mann-Kendall and Regional Mann-Kendall tests. The results showed that the mean annual streamflows of Serra da Mantiqueira En...

Spurious Seasonality Detection: A Non-Parametric Test Proposal

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Aurelio F. Bariviera

2018-01-01

Full Text Available This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called “day-of-the-week” effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.

Nonparametric tests for equality of psychometric functions.

Science.gov (United States)

García-Pérez, Miguel A; Núñez-Antón, Vicente

2017-12-07

Many empirical studies measure psychometric functions (curves describing how observers' performance varies with stimulus magnitude) because these functions capture the effects of experimental conditions. To assess these effects, parametric curves are often fitted to the data and comparisons are carried out by testing for equality of mean parameter estimates across conditions. This approach is parametric and, thus, vulnerable to violations of the implied assumptions. Furthermore, testing for equality of means of parameters may be misleading: Psychometric functions may vary meaningfully across conditions on an observer-by-observer basis with no effect on the mean values of the estimated parameters. Alternative approaches to assess equality of psychometric functions per se are thus needed. This paper compares three nonparametric tests that are applicable in all situations of interest: The existing generalized Mantel-Haenszel test, a generalization of the Berry-Mielke test that was developed here, and a split variant of the generalized Mantel-Haenszel test also developed here. Their statistical properties (accuracy and power) are studied via simulation and the results show that all tests are indistinguishable as to accuracy but they differ non-uniformly as to power. Empirical use of the tests is illustrated via analyses of published data sets and practical recommendations are given. The computer code in MATLAB and R to conduct these tests is available as Electronic Supplemental Material.

Trend of suspended sediment load in the Velika Morava River in the period 1967-2007

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Mustafić Sanja

2014-01-01

Full Text Available The paper is concerned with identifying changes in the time series of discharge (Q, suspended sediment concentration (SSC and sediment load (Qs of the Velika Morva River. The catchment area on farthest hydrological profile Ljubičevski most on Velika Morava River is approximately 35,496 km2. In this profile were carried out daily measurements of flow and concetration of silt in the period from 1967 to 2007. Average perennial transport of suspended sediment is 2.57ˣ106 t (72.4 t/km2/yr and ranged from 0.17ˣ106 t (4.8 t/km2/yr to 10.02ˣ106 t (282.2 t/km2/yr. Trends determined for Q, SSC and Qs are statistically obtained using the non-parametric Mann-Kendall test. Results of Mann-Kendall test show that Q has a slight declining trend of annual values which do not show statistical significance. Decline in trendline SSC and Qs is a significant at the level of 0.01. Calculating the standardized regression coefficients, it was found that the relative impact of SSC on sediment load is 3.1 time higher than the impact of discharge. From 1967 to 2007 the average decrease in sediment load at the mouth of the Velika Morava into the Danube was 3.1 t/km2/yr. [Projekat Ministarstva nauke Republike Srbije, br. 43007: The Research on Climate Change Influences on Environment: Influence Monitoring, Adaptation and Mitigation, subproject No. 9: Torrential Floods Frequency, Soil and Water Degradation as the Consequence of Global Changes

Nonparametric statistics for social and behavioral sciences

CERN Document Server

Kraska-MIller, M

2013-01-01

Introduction to Research in Social and Behavioral SciencesBasic Principles of ResearchPlanning for ResearchTypes of Research Designs Sampling ProceduresValidity and Reliability of Measurement InstrumentsSteps of the Research Process Introduction to Nonparametric StatisticsData AnalysisOverview of Nonparametric Statistics and Parametric Statistics Overview of Parametric Statistics Overview of Nonparametric StatisticsImportance of Nonparametric MethodsMeasurement InstrumentsAnalysis of Data to Determine Association and Agreement Pearson Chi-Square Test of Association and IndependenceContingency

Robust non-parametric one-sample tests for the analysis of recurrent events.

Science.gov (United States)

Rebora, Paola; Galimberti, Stefania; Valsecchi, Maria Grazia

2010-12-30

One-sample non-parametric tests are proposed here for inference on recurring events. The focus is on the marginal mean function of events and the basis for inference is the standardized distance between the observed and the expected number of events under a specified reference rate. Different weights are considered in order to account for various types of alternative hypotheses on the mean function of the recurrent events process. A robust version and a stratified version of the test are also proposed. The performance of these tests was investigated through simulation studies under various underlying event generation processes, such as homogeneous and nonhomogeneous Poisson processes, autoregressive and renewal processes, with and without frailty effects. The robust versions of the test have been shown to be suitable in a wide variety of event generating processes. The motivating context is a study on gene therapy in a very rare immunodeficiency in children, where a major end-point is the recurrence of severe infections. Robust non-parametric one-sample tests for recurrent events can be useful to assess efficacy and especially safety in non-randomized studies or in epidemiological studies for comparison with a standard population. Copyright © 2010 John Wiley & Sons, Ltd.

Nonparametric functional mapping of quantitative trait loci.

Science.gov (United States)

Yang, Jie; Wu, Rongling; Casella, George

2009-03-01

Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

Parametric and nonparametric Granger causality testing: Linkages between international stock markets

Science.gov (United States)

De Gooijer, Jan G.; Sivarajasingham, Selliah

2008-04-01

This study investigates long-term linear and nonlinear causal linkages among eleven stock markets, six industrialized markets and five emerging markets of South-East Asia. We cover the period 1987-2006, taking into account the on-set of the Asian financial crisis of 1997. We first apply a test for the presence of general nonlinearity in vector time series. Substantial differences exist between the pre- and post-crisis period in terms of the total number of significant nonlinear relationships. We then examine both periods, using a new nonparametric test for Granger noncausality and the conventional parametric Granger noncausality test. One major finding is that the Asian stock markets have become more internationally integrated after the Asian financial crisis. An exception is the Sri Lankan market with almost no significant long-term linear and nonlinear causal linkages with other markets. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VAR filtered residuals and VAR filtered squared residuals for the post-crisis sample. We find quite a few remaining significant bi- and uni-directional causal nonlinear relationships in these series. Finally, after filtering the VAR-residuals with GARCH-BEKK models, we show that the nonparametric test statistics are substantially smaller in both magnitude and statistical significance than those before filtering. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects.

Testing a parametric function against a nonparametric alternative in IV and GMM settings

DEFF Research Database (Denmark)

Gørgens, Tue; Wurtz, Allan

This paper develops a specification test for functional form for models identified by moment restrictions, including IV and GMM settings. The general framework is one where the moment restrictions are specified as functions of data, a finite-dimensional parameter vector, and a nonparametric real ...

Nonparametric statistics with applications to science and engineering

CERN Document Server

Kvam, Paul H

2007-01-01

A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provide...

Comparative analysis of automotive paints by laser induced breakdown spectroscopy and nonparametric permutation tests

International Nuclear Information System (INIS)

McIntee, Erin; Viglino, Emilie; Rinke, Caitlin; Kumor, Stephanie; Ni Liqiang; Sigman, Michael E.

2010-01-01

Laser-induced breakdown spectroscopy (LIBS) has been investigated for the discrimination of automobile paint samples. Paint samples from automobiles of different makes, models, and years were collected and separated into sets based on the color, presence or absence of effect pigments and the number of paint layers. Twelve LIBS spectra were obtained for each paint sample, each an average of a five single shot 'drill down' spectra from consecutive laser ablations in the same spot on the sample. Analyses by a nonparametric permutation test and a parametric Wald test were performed to determine the extent of discrimination within each set of paint samples. The discrimination power and Type I error were assessed for each data analysis method. Conversion of the spectral intensity to a log-scale (base 10) resulted in a higher overall discrimination power while observing the same significance level. Working on the log-scale, the nonparametric permutation tests gave an overall 89.83% discrimination power with a size of Type I error being 4.44% at the nominal significance level of 5%. White paint samples, as a group, were the most difficult to differentiate with the power being only 86.56% followed by 95.83% for black paint samples. Parametric analysis of the data set produced lower discrimination (85.17%) with 3.33% Type I errors, which is not recommended for both theoretical and practical considerations. The nonparametric testing method is applicable across many analytical comparisons, with the specific application described here being the pairwise comparison of automotive paint samples.

Estimation from PET data of transient changes in dopamine concentration induced by alcohol: support for a non-parametric signal estimation method

Energy Technology Data Exchange (ETDEWEB)

Constantinescu, C C; Yoder, K K; Normandin, M D; Morris, E D [Department of Radiology, Indiana University School of Medicine, Indianapolis, IN (United States); Kareken, D A [Department of Neurology, Indiana University School of Medicine, Indianapolis, IN (United States); Bouman, C A [Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN (United States); O' Connor, S J [Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN (United States)], E-mail: emorris@iupui.edu

2008-03-07

We previously developed a model-independent technique (non-parametric ntPET) for extracting the transient changes in neurotransmitter concentration from paired (rest and activation) PET studies with a receptor ligand. To provide support for our method, we introduced three hypotheses of validation based on work by Endres and Carson (1998 J. Cereb. Blood Flow Metab. 18 1196-210) and Yoder et al (2004 J. Nucl. Med. 45 903-11), and tested them on experimental data. All three hypotheses describe relationships between the estimated free (synaptic) dopamine curves (F{sup DA}(t)) and the change in binding potential ({delta}BP). The veracity of the F{sup DA}(t) curves recovered by nonparametric ntPET is supported when the data adhere to the following hypothesized behaviors: (1) {delta}BP should decline with increasing DA peak time, (2) {delta}BP should increase as the strength of the temporal correlation between F{sup DA}(t) and the free raclopride (F{sup RAC}(t)) curve increases, (3) {delta}BP should decline linearly with the effective weighted availability of the receptor sites. We analyzed regional brain data from 8 healthy subjects who received two [{sup 11}C]raclopride scans: one at rest, and one during which unanticipated IV alcohol was administered to stimulate dopamine release. For several striatal regions, nonparametric ntPET was applied to recover F{sup DA}(t), and binding potential values were determined. Kendall rank-correlation analysis confirmed that the F{sup DA}(t) data followed the expected trends for all three validation hypotheses. Our findings lend credence to our model-independent estimates of F{sup DA}(t). Application of nonparametric ntPET may yield important insights into how alterations in timing of dopaminergic neurotransmission are involved in the pathologies of addiction and other psychiatric disorders.

Mann-Whitney Type Tests for Microarray Experiments: The R Package gMWT

Directory of Open Access Journals (Sweden)

Daniel Fischer

2015-06-01

Full Text Available We present the R package gMWT which is designed for the comparison of several treatments (or groups for a large number of variables. The comparisons are made using certain probabilistic indices (PI. The PIs computed here tell how often pairs or triples of observations coming from different groups appear in a specific order of magnitude. Classical two and several sample rank test statistics such as the Mann-Whitney-Wilcoxon, Kruskal-Wallis, or Jonckheere-Terpstra test statistics are simple functions of these PI. Also new test statistics for directional alternatives are provided. The package gMWT can be used to calculate the variable-wise PI estimates, to illustrate their multivariate distribution and mutual dependence with joint scatterplot matrices, and to construct several classical and new rank tests based on the PIs. The aim of the paper is first to briefly explain the theory that is necessary to understand the behavior of the estimated PIs and the rank tests based on them. Second, the use of the package is described and illustrated with simulated and real data examples. It is stressed that the package provides a new flexible toolbox to analyze large gene or microRNA expression data sets, collected on microarrays or by other high-throughput technologies. The testing procedures can be used in an eQTL analysis, for example, as implemented in the package GeneticTools.

77 FR 76065 - Endangered and Threatened Wildlife and Plants; Draft Revised Recovery Plan for Kendall Warm...

Science.gov (United States)

2012-12-26

...] Endangered and Threatened Wildlife and Plants; Draft Revised Recovery Plan for Kendall Warm Springs Dace... revised recovery plan for the Kendall Warm Springs dace (Rhinichthys osculus thermalis). This species is... recovery plan. The Kendall Warm Springs dace (Rhinichthys osculus thermalis), found only in one location in...

Keanekaragaman Jenis Kupu-Kupu Superfamili Papilionoidae di Banyuwindu, Limbangan Kendal

Directory of Open Access Journals (Sweden)

Ratna Oqtafiana

2013-03-01

Full Text Available Kupu-kupu turut memberi andil dalam mempertahankan keseimbangan ekosistem dan memperkaya keanekaragaman hayati. Tujuan dari penelitian ini adalah untuk mengetahui keanekaragaman jenis kupu-kupu superfamili Papilionoidae di Dukuh Banyuwindu Desa Limbangan Kecamatan Limbangan Kabupaten Kendal khususnya di habitat hutan sekunder, permukiman, Daerah Aliran Sungai (DAS dan persawahan.Populasi dalam penelitian ini adalah semua jenis kupu-kupu superfamili Papilionoidae yang ada di Banyuwindu, Limbangan Kendal. Sampel penelitian ini adalah jenis kupu-kupu superfamili Papilionoidae yang teramati di Banyuwindu Limbangan Kendal khususnya di habitat hutan sekunder, permukiman, DAS dan persawahan. Penelitian dilakukan dengan metode Indeks Point Abudance (IPA atau metode titik hitung.Hasil penelitian ditemukan sebanyak 62 jenis kupu-kupu superfamili Papilionoidae yang terdiri dari 737 individu yang tergolong kedalam empat famili yaitu Papilionidae, Pieridae, Lycaenidae dan Nymphalidae. Hasil analisis indeks keanekaragaman jenis berkisar antara 2,74-3,09, indeks kemerataan jenis berkisar antara 0,86-0,87 dan memiliki dominansi berkisar antara 0,07-0,09. Indeks keanekaragaman jenis dan indeks kemerataan jenis tertinggi tercatat pada habitat permukiman yaitu 3,09 dan 0,87 dan memiliki dominansi 0,07 sedangkan terendah tercatat pada habitat persawahan yaitu 2,74 dan 0,86 dan memiliki dominansi 0,07.Butterfly also contribute in maintaining the ecological balance and enrich biodiversity. The aim of this research was to determine the diversity of butterflies’ superfamily Papilionoidae in Banyuwindu Hamlet Limbangan Sub district Kendal Regency, especially in the secondary forest habitat, settlements, river flow area (RFA and rice field. The population in this research were all kinds of butterflies’ Papilionoidae superfamily in Banyuwindu, Limbangan Kendal. The sample was kind of butterfly superfamily Papilionoidae that observed in Banyuwindu Limbangan Kendal

Klaus Mann's Mephisto: A Secret Rivalry

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Peter T. Hoffer

1989-08-01

Full Text Available Critics of the 1960s and 1970s have focused their attention on Klaus Mann's use of his former brother-in-law, Gustaf Gründgens, as the model for the hero of his controversial novel, Mephisto , while more recent critics have emphasized its significance as a work of anti-Fascist literature. This essay seeks to resolve some of the apparent contradictions in Klaus Mann's motivation for writing Mephisto by viewing the novel primarily in the context of his life and career. Although Mephisto is the only political satire that Klaus Mann wrote, it is consistent with his life-long tendency to use autobiographical material as the basis for much of his plot and characterization. Mann transformed his ambivalent feelings about Gründgens, which long antedated the writing of Mephisto , into a unique work of fiction which simultaneously expresses his indignation over the moral bankruptcy of the Third Reich and reveals his envy of Gründgens's career successes.

Introduction to nonparametric statistics for the biological sciences using R

CERN Document Server

MacFarland, Thomas W

2016-01-01

This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses a...

Climate Verification Using Running Mann Whitney Z Statistics

Science.gov (United States)

A robust method previously used to detect observed intra- to multi-decadal (IMD) climate regimes was adapted to test whether climate models could reproduce IMD variations in U.S. surface temperatures during 1919-2008. This procedure, called the running Mann Whitney Z (MWZ) method, samples data ranki...

Nonparametric identification of copula structures

KAUST Repository

Li, Bo; Genton, Marc G.

2013-01-01

We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric

ORANG KALANG DAN BUDAYANYA: TINJAUAN HISTORIS MASYARAKAT KALANG DI KABUPATEN KENDAL

Directory of Open Access Journals (Sweden)

Muslichin Muslichin

2011-10-01

Full Text Available This paper aims to explore and explain the history of Kalangse community in Kendal Regency. In the past, Kalang people occupied a minority position in the history. As time passes, they can show the real social position. History of the Kalang contained in the Village District Poncorejo Gemuh Kendal District at least give a concrete picture of how the development of cultural existence of these groups to influence the changing times. What happens in Poncorejo provide a portrait of community life, especially community that occupy other coastal areas in Kendal regency. Kalang people who in the Hindu-Buddhist kingdom do not get social status equal with other ethnic groups because of different cultural backgrounds or are considered untouchable, are recognized bt the Dutch colonial as more special because of the ethos and work performance in accordance with the spirit of colonial development. The dark and boring history of communist life, finally becomes normal due to the effort of the policy of Dutch Colonial which recognized the equality of basic right for them, spreading of Islam, and the influence of modernization and globalization in this periode.   Key words: Kalangese, Culture, and Religion   Makalah ini bertujuan untuk mengeksplorasi dan menjelaskan sejarah masyarakat Kalang di Kabupaten Kendal. Di masa lalu, orang Kalang menempati posisi minoritas dalam sejarah. Dengan berjalannya waktu, mereka dapat menunjukkan posisi sosial yang nyata. Sejarah Kalang terutama di Desa Gemuh Kendal Poncorejo setidaknya memberikan gambaran konkret bagaimana perkembangan keberadaan budaya dari kelompok-kelompok itu untuk mempengaruhi perubahan zaman. Apa yang terjadi di Poncorejo memberi potret kehidupan masyarakat, terutama yang menempati daerah pesisir lainnya di Kabupaten Kendal sendiri. Orang Kalang pada masa Hindu-Buddha tidak mendapatkan status sosial yang sepadan dengan kelompok etnis lain karena latar belakang budaya yang berbeda atau

Assessment of Fluctuation Patterns Similarity in Temperature and Vapor Pressure Using Discrete Wavelet Transform

Directory of Open Access Journals (Sweden)

A. Araghi

2014-12-01

Full Text Available Period and trend are two main effective and important factors in hydro-climatological time series and because of this importance, different methods have been introduced and applied to study of them, until now. Most of these methods are statistical basis and they are classified in the non-parametric tests. Wavelet transform is a mathematical based powerful method which has been widely used in signal processing and time series analysis in recent years. In this research, trend and main periodic patterns similarity in temperature and vapor pressure has been studied in Babolsar, Tehran and Shahroud synoptic stations during 55 years period (from 1956 to 2010, using wavelet method and the sequential Mann-Kendall trend test. The results show that long term fluctuation patterns in temperature and vapor pressure have more correlations in the arid and semi-arid climates, as well as short term oscillation patterns in temperature and vapor pressure in the humid climates, and these dominant periods increase with the aridity of region.

Cholera in Thomas Mann's Death in Venice.

Science.gov (United States)

Rütten, Thomas

2009-01-01

The article sets the cholera motif in Thomas Mann's famous novella Death in Venice against the historical context from which it partially originates. It is shown that this motif, while undoubtedly appropriated to serve Mann's own poetic ends, has a solid grounding in historical and autobiographical fact, thus blurring the boundaries between fact and fiction. The article illustrates the verifiable events of the outbreak of the Venetian cholera epidemic in May 1911, which Mann partly witnessed himself, during a holiday trip to Brioni and Venice, and partly heard and read about. It is established that Thomas Mann's account of the cholera in Venice in his novella is characterised by a rare and almost preternatural insightfulness into an otherwise murky affair that was marked by rumours, speculations and denials.

K2 and K2*: efficient alignment-free sequence similarity measurement based on Kendall statistics.

Science.gov (United States)

Lin, Jie; Adjeroh, Donald A; Jiang, Bing-Hua; Jiang, Yue

2018-05-15

Alignment-free sequence comparison methods can compute the pairwise similarity between a huge number of sequences much faster than sequence-alignment based methods. We propose a new non-parametric alignment-free sequence comparison method, called K2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K2 demonstrates competitive performance in generating the phylogenetic tree, in evaluating functionally related regulatory sequences, and in computing the edit distance (similarity/dissimilarity) between sequences. Furthermore, the K2 approach is much faster than the other methods. An improved method, K2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automatically, without first considering different values. Comparative analysis with the state-of-the-art alignment-free sequence similarity methods demonstrates the superiority of the proposed approaches, especially with increasing sequence length, or increasing dataset sizes. The K2 and K2* approaches are implemented in the R language as a package and is freely available for open access (http://community.wvu.edu/daadjeroh/projects/K2/K2_1.0.tar.gz). yueljiang@163.com. Supplementary data are available at Bioinformatics online.

Observed changes in relative humidity and dew point temperature in coastal regions of Iran

Science.gov (United States)

Hosseinzadeh Talaee, P.; Sabziparvar, A. A.; Tabari, Hossein

2012-12-01

The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann-Kendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature ( T dew) time series at ten coastal weather stations in Iran during 1966-2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28 %/decade at the northern and southern coastal regions of the country, respectively, while annual T dew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the T dew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and T dew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.

Assessing the Priority Area of Mountainous Tourism Using Geospatial Approach in Kendal Regency, Central Java

Science.gov (United States)

Riwayatiningsih; Purnaweni, Hartuti

2018-02-01

Kendal is one of 35 regencies in Central Java which has diverse topographies, from low land, hilly, to mountainous areas. Mountainous area of Kendal with numerous unique and distinct natural environments, supported by various unique and distinct culture of its community can be used for tourism activities. Kendal has natural and sociocultural resources for developing tourism that must be considered by the local government. Therefore, nature based tourism resources assessment is important in order to determine the appropriate area in the planning of sustainable tourism destination. The objectives of this study are to assess and prioritize the potential area of mountainous tourism object in Kendal using geospatial approach based on criteria attractiveness, accessibility and amenity of the tourism object. Those criteria are modification of ADO-ODTWA guidelines and condition of the study location. There are 16 locations of tourism object that will be assessed. The result will be processed using ArcMap 10.3. The result will show the most potential tourism object that could become priority for mountainous tourism development in Kendal.

Nonparametric statistical inference

CERN Document Server

Gibbons, Jean Dickinson

2010-01-01

Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente

Efficiency Analysis of German Electricity Distribution Utilities : Non-Parametric and Parametric Tests

OpenAIRE

von Hirschhausen, Christian R.; Cullmann, Astrid

2005-01-01

Abstract This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) ...

Nonparametric Bayes Classification and Hypothesis Testing on Manifolds

Science.gov (United States)

Bhattacharya, Abhishek; Dunson, David

2012-01-01

Our first focus is prediction of a categorical response variable using features that lie on a general manifold. For example, the manifold may correspond to the surface of a hypersphere. We propose a general kernel mixture model for the joint distribution of the response and predictors, with the kernel expressed in product form and dependence induced through the unknown mixing measure. We provide simple sufficient conditions for large support and weak and strong posterior consistency in estimating both the joint distribution of the response and predictors and the conditional distribution of the response. Focusing on a Dirichlet process prior for the mixing measure, these conditions hold using von Mises-Fisher kernels when the manifold is the unit hypersphere. In this case, Bayesian methods are developed for efficient posterior computation using slice sampling. Next we develop Bayesian nonparametric methods for testing whether there is a difference in distributions between groups of observations on the manifold having unknown densities. We prove consistency of the Bayes factor and develop efficient computational methods for its calculation. The proposed classification and testing methods are evaluated using simulation examples and applied to spherical data applications. PMID:22754028

A new powerful non-parametric two-stage approach for testing multiple phenotypes in family-based association studies

NARCIS (Netherlands)

Lange, C; Lyon, H; DeMeo, D; Raby, B; Silverman, EK; Weiss, ST

2003-01-01

We introduce a new powerful nonparametric testing strategy for family-based association studies in which multiple quantitative traits are recorded and the phenotype with the strongest genetic component is not known prior to the analysis. In the first stage, using a population-based test based on the

Generative Temporal Modelling of Neuroimaging - Decomposition and Nonparametric Testing

DEFF Research Database (Denmark)

Hald, Ditte Høvenhoff

The goal of this thesis is to explore two improvements for functional magnetic resonance imaging (fMRI) analysis; namely our proposed decomposition method and an extension to the non-parametric testing framework. Analysis of fMRI allows researchers to investigate the functional processes...... of the brain, and provides insight into neuronal coupling during mental processes or tasks. The decomposition method is a Gaussian process-based independent components analysis (GPICA), which incorporates a temporal dependency in the sources. A hierarchical model specification is used, featuring both...... instantaneous and convolutive mixing, and the inferred temporal patterns. Spatial maps are seen to capture smooth and localized stimuli-related components, and often identifiable noise components. The implementation is freely available as a GUI/SPM plugin, and we recommend using GPICA as an additional tool when...

Murray Gell-Mann and the physics of quarks

CERN Document Server

2018-01-01

Murray Gell-Mann, Physics Nobel Prize Laureate in 1969 is known for his theoretical work on elementary particle physics and the introduction of quarks and together with H. Fritzsch the “Quantum Chromodynamics”. Based on four sections the Editor gives an overview on the work of Gell-Mann and his contributions to various aspects of the physics, related to quarks. His most important and influential papers were selected and reprinted so that the reader easily can check the original work of Gell-Mann.

Simple nonparametric checks for model data fit in CAT

NARCIS (Netherlands)

Meijer, R.R.

2005-01-01

In this paper, the usefulness of several nonparametric checks is discussed in a computerized adaptive testing (CAT) context. Although there is no tradition of nonparametric scalability in CAT, it can be argued that scalability checks can be useful to investigate, for example, the quality of item

On the Symbolism of Thomas Mann

Directory of Open Access Journals (Sweden)

Vasily M. Tolmatchoff

2017-09-01

Full Text Available The essay discusses Thomas Mann’s symbolism and its parameters as well as Mann’s interpretation of the crisis of European spiritual values. Тhe author examines the role of Nietzsche in Mann’s heritage as well as interconnections between Mann and Wilde, Mann and Gide. Buddenbrooks is interpreted as a novel about the end of the German Renaissance; duality of the modern artist is shown on the example of “Tonio Kröger” while the paradoxes of his eroticism are analyzed on the example of “Der Tod in Venedig.”

Diurnal temperature range trend over North Carolina and the associated mechanisms

Science.gov (United States)

Sayemuzzaman, Mohammad; Mekonnen, Ademe; Jha, Manoj K.

2015-06-01

This study seeks to investigate the variability and presence of trend in the diurnal surface air temperature range (DTR) over North Carolina (NC) for the period 1950-2009. The significance trend test and the magnitude of trends were determined using the non-parametric Mann-Kendall test and the Theil-Sen approach, respectively. Statewide significant trends (p < 0.05) of decreasing DTR were found in all seasons and annually during the analysis period. Highest (lowest) temporal DTR trends of magnitude - 0.19 (- 0.031) °C/decade were found in summer (winter). Potential mechanisms for the presence/absence of trend in DTR have been highlighted. Historical data sets of the three main moisture components (precipitation, total cloud cover (TCC), and soil moisture) and the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for correlation analysis. The DTRs were found to be negatively correlated with the precipitation, TCC and soil moisture across the state for all the seasons and annual basis. It appears that the moisture components related better to the DTR than to the atmospheric circulation modes.

IbM BAGI GURU MATEMATIKA SMPDI KABUPATEN KENDAL

Directory of Open Access Journals (Sweden)

Rasiman .

2015-07-01

Full Text Available Abstract Community service activities for this, intended for junior high school mathematics teachers, especially in MGMPs Kendal in support of Curriculum 2013. The 2013 curriculum is implemented in stages beginning in school year 2013-2014 through the implementation is limited, especially for schools that are ready to implement it. In the academic year of 2013/2014, Curriculum 2013 implemented on a limited basis for Class I and IV Elementary / Madrasah Ibtida'iyah (SD / MI, Class VII School SMP / MTs (SMP / MTs, and Class X High School / School SMK / Madrasah Aliyah (SMA / SMK / MA / MAK. In the academic year of 2015/2016 is expected toCurriculum 2013 has been implemented in the whole class I to Class XII. For that we consider necessary the holding of training activities and workshops preparation of lesson plans and training curriculum in 2013 based learning media creation software GeoGebra useful for teachers of Mathematics junior in Kendal. The method used is the training and workshops with a target output of each participant design a lesson plan curriculum in 2013 and the manufacture of Mathematics instructional media with the help of software GeoGebra. Keywords: Curriculum 2013, GeoGebra

Nonparametric test of consistency between cosmological models and multiband CMB measurements

Energy Technology Data Exchange (ETDEWEB)

Aghamousa, Amir [Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk 790-784 (Korea, Republic of); Shafieloo, Arman, E-mail: amir@apctp.org, E-mail: shafieloo@kasi.re.kr [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of)

2015-06-01

We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare between the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles  18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.

Statistical significance of trends in monthly heavy precipitation over the US

KAUST Repository

Mahajan, Salil; North, Gerald R.; Saravanan, R.; Genton, Marc G.

2011-01-01

-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall's τ test, implying the robustness of the approach. Two different observational data

Nonparametric statistical inference

CERN Document Server

Gibbons, Jean Dickinson

2014-01-01

Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

On the stationarity of annual flood peaks in the continental United States during the 20th century

Science.gov (United States)

Villarini, Gabriele; Serinaldi, Francesco; Smith, James A.; Krajewski, Witold F.

2009-08-01

Annual peak discharge records from 50 stations in the continental United States with at least 100 years of record are used to investigate stationarity of flood peaks during the 20th century. We examine temporal trends in flood peaks and abrupt changes in the mean and/or variance of flood peak distributions. Change point analysis for detecting abrupt changes in flood distributions is performed using the nonparametric Pettitt test. Two nonparametric (Mann-Kendall and Spearman) tests and one parametric (Pearson) test are used to detect the presence of temporal trends. Generalized additive models for location, scale, and shape (GAMLSS) are also used to parametrically model the annual peak data, exploiting their flexibility to account for abrupt changes and temporal trends in the parameters of the distribution functions. Additionally, the presence of long-term persistence is investigated through estimation of the Hurst exponent, and an alternative interpretation of the results in terms of long-term persistence is provided. Many of the drainage basins represented in this study have been affected by regulation through systems of reservoirs, and all of the drainage basins have experienced significant land use changes during the 20th century. Despite the profound changes that have occurred to drainage basins throughout the continental United States and the recognition that elements of the hydrologic cycle are being altered by human-induced climate change, it is easier to proclaim the demise of stationarity of flood peaks than to prove it through analyses of annual flood peak data.

A comprehensive analysis of physiologically equivalent temperature changes of Iranian selected stations for the last half century

Science.gov (United States)

Roshan, Gholamreza; Yousefi, Robabe; Kovács, Attila; Matzarakis, Andreas

2018-01-01

As a preliminary and major step for land use planning of the coming years, the study of variability of the past decades' climatic conditions with comprehensive indicators is of high importance. Given the fact that one of the affected areas by climatic change includes variability of thermal comfort, this study uses the physiologically equivalent temperature (PET) to identify and evaluate bioclimatic conditions of 40 meteorological stations in Iran. In this study, PET changes for the period of 1960 to 2010 are analyzed, with the use of Mann-Kendall non-parametric test and Pearson parametric method. The study focuses particularly on the diversity in spatio-temporal distribution of Iran's bioclimatic conditions. The findings show that the mean frequency percentage of days with comfort is 12.9 % according to the total number of selected stations. The maximum and minimum frequency percentage with values of 17.4 and 10.3 belong to Kerman and Chabahar stations, respectively. The findings of long-term trend analysis for the period of 1960-2010 show that 55 % of the stations have significant increasing trend in terms of thermal comfort class based on the Pearson method, while it is 40 % based on Mann-Kendall test. The results indicate that the highest frequency of days with thermal comfort in the southern coasts of Iran relates to the end of autumn and winter, nevertheless, such ideal conditions for the coastal cities of Caspian Sea and even central stations of Iran relate to mid-spring and mid-autumn. Late summer and early autumn along with late spring can be identified as the most ideal times in the west and northwest part of Iran. In addition, the most important inhibiting factors of thermal comfort prove to be different across the regions of Iran. For instance, in the southern coasts, warm to very hot bioclimatic events and in the west and northwest regions, cold to very cold conditions turn out to be the most important inhibiting factors. When considering the variations

An Interview with Joe McMann: His Life Lessons

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McMann, Joe

2011-01-01

Pica Kahn conducted "An Interview with Joe McMann: His Life Lessons" on May 23, 2011. With over 40 years of experience in the aerospace industry, McMann has gained a wealth of knowledge. Many have been interested in his biography, progression of work at NASA, impact on the U.S. spacesuit, and career accomplishments. This interview highlighted the influences and decision-making methods that impacted his technical and management contributions to the space program. McMann shared information about the accomplishments and technical advances that committed individuals can make.

Nonparametric predictive inference for combining diagnostic tests with parametric copula

Science.gov (United States)

Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

2017-09-01

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

2nd Conference of the International Society for Nonparametric Statistics

CERN Document Server

Manteiga, Wenceslao; Romo, Juan

2016-01-01

This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers...

Trends in rainfall and rainfall-related extremes in the east coast of ...

Indian Academy of Sciences (India)

Malaysia have been analyzed using the non-parametric Mann–Kendall test and the Sen's slope method. The Monte .... and the Sen's slope method (Sen 1968) is used to determine ...... S A and Aziz N A A 2009 Issues of climate change and.

SOSIALISASI SCHOOL BULLYING SEBAGAI UPAYA PREVENTIF TERJADINYA TINDAK PIDANA KEKERASAN DI SMPN 3 BOJA KABUPATEN KENDAL

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Anis Widyawati

2014-12-01

Full Text Available Perilaku bullying sebenarnya sudah sangat meluas di dunia pendidikan kita tanpa terlalu kita sadari bentuk dan akibatnya. Dalam bagian kedua, penulis akan menulusuri beberapa sumber lebih jauh lagi untuk melihat karakteristik pelaku bullying, mitos dan fakta tentang bullying, serta bagaimana menghadapi bullying, baik bagi korban, siswa lain yang menonton, maupun bagi pihak sekolah atau orang tua. Berdasarkan latar belakang diatas dapat dirumuskan permasalahan yaitu Bagaimana bentuk-bentuk perbuatan school bullying yang terjadi di SMP 3 Boja Kecamatan Boja Kabupaten Kendal dan Bagaimana pendekatan Restorative Justice dalam menyelesaikan kasus school bullying. Dalam kegiatan pengabdian ini, metode yang digunakan adalah dengan model penyuluhan dan dialog interaktif sehingga selain memberikan informasi tentang pemahaman sosialisasi school bullying sebagai upaya preventif terjadinya tindak pidana kekerasan di smpn 3 boja kabupaten kendal, masyarakat juga ikut aktif dalam dialog agar tidak merasa bosan sehingga terjalinnya komunikasi yang baik. Berdasarkan pengamatan selama melakukan pengabdian tim melihat keseriusan dan antusias peserta dalam mengikuti penjelasan mengenai sosialisasi school bullying sebagai upaya preventif terjadinya tindak pidana kekerasan di SMPN 3 boja kabupaten kendal. Peserta juga aktif dalam menanggapi dan merespon penjelasan pemateri. Tim pengabdian memberikan saran agar kegiatan sosialisasi mengenai sosialisasi school bullying sebagai upaya preventif terjadinya tindak pidana kekerasan di smpn 3 boja kabupaten kendal dilaksanakan secara terus menerus dan konsisten serta melibatkan stake holders yang terkait yaitu Dinas Pendidikan Kendal dan SMPN 3 Boja, karena jarang sosialisasi tentang tema tersebut.

Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida

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Sayemuzzaman, M.; Ye, M.

2015-12-01

The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

Science.gov (United States)

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nonparametric identification of copula structures

KAUST Repository

Li, Bo

2013-06-01

We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process.We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particularly when the sample size is moderately large. We illustrate our testing approach on two datasets. © 2013 American Statistical Association.

A nonparametric spatial scan statistic for continuous data.

Science.gov (United States)

Jung, Inkyung; Cho, Ho Jin

2015-10-20

Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

Mapping trends of large and medium size carnivores of conservation interest in Romania

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Constantin Cazacu

2014-07-01

Full Text Available We analysed yearly estimates of population size data during 2001-2012 for five carnivores species of conservation interest (Ursus arctos, Canis lupus, Lynx lynx, Felis silvestris and Canis aureus. Population size estimations were done by the game management authorities and integrated by the competent authorities on the Ministry of Environment and Climate Change. Trends in data were detected using non-parametric Mann-Kendall test. This test was chosen considering the short length of data series and its usefulness for non-normal distributed data. The trend was tested at three spatial scales: game management units (n=1565, biogeographical region (n=5 and national. Trends depicted for each game management unit were plotted using ArcGIS, resulting species trend distribution maps. For the studied period increasing population trends were observed for Ursus arctos, Canis lupus, Canis aureus and Lynx lynx, while for Felis silvestris there was no trend recorded. Such an analysis in especially useful for conservation proposes, game management and reporting obligations under article 17 of the EC Habitat Directive, using population trend as a proxy for population dynamics. We conclude that the status of the five carnivore species is favourable during the study period.

Annual baseflow variations as influenced by climate variability and agricultural land use change in the Missouri River basin

Science.gov (United States)

Detection of changes (steady or abrupt) in long time series of hydrological data is important for effective planning and management of water resources. This study evaluated trends in baseflow and precipitation in the Missouri River Basin (MORB) using a modified Mann-Kendall (MK) test. Precipitation ...

The geometry of distributional preferences and a non-parametric identification approach: The Equality Equivalence Test.

Science.gov (United States)

Kerschbamer, Rudolf

2015-05-01

This paper proposes a geometric delineation of distributional preference types and a non-parametric approach for their identification in a two-person context. It starts with a small set of assumptions on preferences and shows that this set (i) naturally results in a taxonomy of distributional archetypes that nests all empirically relevant types considered in previous work; and (ii) gives rise to a clean experimental identification procedure - the Equality Equivalence Test - that discriminates between archetypes according to core features of preferences rather than properties of specific modeling variants. As a by-product the test yields a two-dimensional index of preference intensity.

Subseasonal climate variability for North Carolina, United States

Science.gov (United States)

Sayemuzzaman, Mohammad; Jha, Manoj K.; Mekonnen, Ademe; Schimmel, Keith A.

2014-08-01

Subseasonal trends in climate variability for maximum temperature (Tmax), minimum temperature (Tmin) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The magnitude and significance of the trends at all stations were determined using the non-parametric Theil-Sen Approach (TSA) and the Mann-Kendall (MK) test, respectively. The Sequential Mann-Kendall (SQMK) test was also applied to find the initiation of abrupt trend changes. The lag-1 serial correlation and double mass curve were employed to address the data independency and homogeneity. Using the MK trend test, statistically significant (confidence level ≥ 95% in two-tailed test) decreasing (increasing) trends by 44% (45%) of stations were found in May (June). In general, trends were decreased in Tmax and increased in Tmin data series in subseasonal scale. Using the TSA method, the magnitude of lowest (highest) decreasing (increasing) trend in Tmax is - 0.050 °C/year (+ 0.052 °C/year) in the monthly series for May (March) and for Tmin is - 0.055 °C/year (+ 0.075 °C/year) in February (December). For the precipitation time series using the TSA method, it was found that the highest (lowest) magnitude of 1.00 mm/year (- 1.20 mm/year) is in September (February). The overall trends in precipitation data series were not significant at the 95% confidence level except that 17% of stations were found to have significant (confidence level ≥ 95% in two-tailed test) decreasing trends in February. The statistically significant trend test results were used to develop a spatial distribution of trends: May for Tmax, June for Tmin, and February for precipitation. A correlative analysis of significant temperature and precipitation trend results was examined with respect to large scale circulation modes (North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI). A negative NAO index (positive-El Niño Southern Oscillation (ENSO) index) was found to be associated with

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

Science.gov (United States)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

A non-parametric consistency test of the ΛCDM model with Planck CMB data

Energy Technology Data Exchange (ETDEWEB)

Aghamousa, Amir; Shafieloo, Arman [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of); Hamann, Jan, E-mail: amir@aghamousa.com, E-mail: jan.hamann@unsw.edu.au, E-mail: shafieloo@kasi.re.kr [School of Physics, The University of New South Wales, Sydney NSW 2052 (Australia)

2017-09-01

Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.

Producción arrocera y evolución de elementos climáticos en la provincia de Corrientes (Argentina

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Scarpati, Olga Eugenia

2016-06-01

Full Text Available Rice, a traditional crop in Corrientes (Argentine Republic, has shown variations in production in recent decades so an analysis to detect whether they were due to climate change or other factors is performed. Provincial production data come from the Ministry of Agriculture, Livestock and Fisheries. Daily temperature and precipitation data belong to the National Meteorological Service and the National Institute of Agricultural Technology. The results were validated with the nonparametric tests Mann Kendall and Sen. The results show a clear increase in rice production. Climatic elements demostrate an increase in some values of mean maximum temperature and mean minimum and a precipitation decrease in some months. No major climate changes are detected in the last forty years al the level of the statistical model used, so changes were inferred in external demand.El arroz, cultivo tradicional en Corrientes (República Argentina, ha mostrado variaciones en su producción en las últimas décadas por lo que se realiza un análisis a fin de detectar si ellos se debieron a cambios climáticos o a otros factores. Los datos del cultivo provienen del Ministerio de Agricultura, Ganadería y Pesca. Los datos diarios de temperatura y precipitación pertenecen al Servicio Meteorológico Nacional y al Instituto Nacional de Tecnología Agropecuaria. Los resultados fueron validados con los tests no paramétrico Mann Kendall y Sen. Los resultados muestran un evidente aumento de la producción arrocera. Los elementos climáticos señalan un incremento en algunos valores de la temperatura media máxima y de la media mínima y una disminución de la precipitación en algunos meses. No se detectan cambios importantes del clima en los últimos cuarenta años al nivel del modelo estadístico utilizado, por lo que se infiere modificaciones en la demanda externa.

[A summer afternoon in Grinzing. Thomas Mann visits Sigmund Freud].

Science.gov (United States)

Hummel, Gerhard

2006-01-01

Focussing on June 14th, 1936 when Mann visited Freud to read him the speech he had delivered in Vienna in celebration of Freud's 80th birthday, the paper investigates the "less than simple" relation between the two men. It shows how they gradually approached each other and then in 1929 entered into direct contact after Mann had publicly underlined Freud's relevance for his project "psychology and myth". Some traces of personal ambivalence contained in the 1936 lecture are highlighted. The author discusses the potential significance for both men of Freud's response to Mann's speech where he interpreted aspects of Napoleon's life as based on his identification with the biblical Joseph in order to surpass his elder brother. Finally it is considered whether Mann's contact with Freud may have helped him to cope with the trauma of the early loss of his father.

Tendência das séries temporais de precipitação da região sul do Brasil

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Adilson Pinheiro

2013-09-01

Full Text Available O objetivo deste trabalho é avaliar a presença de tendências nas séries temporais de precipitação no Sul do Brasil. Foram analisadas séries temporais diárias, mensais e anuais de 18 estações pluviométricas. As distribuições de probabilidade normal e de extremos tipo I foram empregadas para análise dos dados. Foi, ainda, aplicado o teste de tendência de Mann-Kendall na detecção de tendências ou de variabilidades climáticas. Os resultados mostram uma tendência positiva dos máximos diários anuais ao longo do tempo, assim como significativa elevação dos totais mensais e anuais na maioria das estações. O teste de tendência de Mann-Kendal mostra mudanças estatisticamente significativas, ao nível de 95%, em 16 das 18 estações pluviométricas analisadas.

Rainfall and runoff regime trends in mountain catchments (Case study area: the upper Hron River basin, Slovakia

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Blahušiaková Andrea

2015-09-01

Full Text Available This paper presents an analysis of trends and causes of changes of selected hydroclimatic variables influencing the runoff regime in the upper Hron River basin (Slovakia. Different methods for identifying trends in data series are evaluated and include: simple mass curve analysis, linear regression, frequency analysis of flood events, use of the Indicators of Hydrological Alteration software, and the Mann-Kendall test. Analyses are performed for data from two periods (1931-2010 and 1961-2010. The changes in runoff are significant, especially in terms of lower QMax and 75 percentile values. This fact is also confirmed by the lower frequency and extremity of flood events. The 1980s are considered a turning point in the development of all hydroclimatic variables. The Mann-Kendall test shows a significant decrease in runoff in the winter period. The main causes of runoff decline are: the considerable increase in air temperature, the decrease in snow cover depth and changes in seasonal distribution of precipitation amounts.

Nonparametric Inference for Periodic Sequences

KAUST Repository

Sun, Ying

2012-02-01

This article proposes a nonparametric method for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both theoretically and by simulation.We also propose a nonparametric test of the null hypothesis that the data have constantmean against the alternative that the sequence of means is periodic. Finally, our methodology is demonstrated on three well-known time series: the sunspots and lynx trapping data, and the El Niño series of sea surface temperatures. © 2012 American Statistical Association and the American Society for Quality.

Trend analysis of hydro-climatic variables in the north of Iran

Science.gov (United States)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

Murray Gell-Mann, the Eightfold Way, Quarks, and Quantum Chromodynamics

Science.gov (United States)

. Professor Gell-Mann's "eightfold way" theory brought order to the chaos created by the discovery , Professor Gell-Mann received the Nobel Prize in physics for his work on the theory of elementary particles later constructed the quantum field theory of quarks and gluons, called "quantum chromodynamics

Time Series Analysis Based on Running Mann Whitney Z Statistics

Science.gov (United States)

A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...

Comparing parametric and nonparametric regression methods for panel data

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

Flood Risk Characterization for the Eastern United States

Science.gov (United States)

Villarini, G.; Smith, J. A.; Ntelekos, A. A.

2009-04-01

Tropical cyclones landfalling in the eastern United States pose a major risk for insured property and can lead to extensive damage through storm surge flooding, inland flooding or extreme windspeeds. Current hurricane cat-models do not include calculations of inland flooding from the outer rainfall bands of tropical cyclones but the issue is becoming increasingly important for commercial insurance risk assessment. The results of this study could be used to feed into the next generation of hurricane cat-models and assist in the calculation of damages from inland hurricane flood damage. Annual maximum peak discharge records from more than 400 stations in the eastern United States with at least 75 years of record to examine the role of landfalling tropical cyclones in controlling the upper tail of inland flood risk for the eastern United States. In addition to examining tropical cyclone inland flood risk at specific locations, the spatial extent of extreme flooding from lanfalling tropical cyclones is analyzed. Analyses of temporal trends and abrupt changes in the mean and variance of annual flood peaks are performed. Change-point analysis is performed using the non-parametric Pettitt test. Two non-parametric (Mann-Kendall and Spearman) tests and one parametric (Pearson) test are applied to detect the presence of temporal trends. Flood risk characterization centers on assessments of the spatial variation in "upper tail" properties of annual flood peak distributions. The modeling framework for flood frequency analysis is provided by the Generalized Additive Models for Location Scale and Shape (GAMLSS).

Assessment of land degradation using time series trend analysis of vegetation indictors in Otindag Sandy land

International Nuclear Information System (INIS)

Wang, H Y; Li, Z Y; Gao, Z H; Wu, J J; Sun, B; Li, C L

2014-01-01

Land condition assessment is a basic prerequisite for finding the degradation of a territory, which might lead to desertification under climatic and human pressures. The temporal change in vegetation productivity is a key indicator of land degradation. In this paper, taking the Otindag Sandy Land as a case, the mean normalized difference vegetation index (NDVI a ), net primary production (NPP) and vegetation rain use efficiency (RUE) dynamic trends during 2001–2010 were analysed. The Mann-Kendall test and the Correlation Analysis method were used and their sensitivities to land degradation were evaluated. The results showed that the three vegetation indicators (NDVI a , NPP and RUE) showed a downward trend with the two methods in the past 10 years and the land was degraded. For the analysis of the three vegetation indicators (NDVI a , NPP and RUE), it indicated a decreasing trend in 62.57%, 74.16% and 88.56% of the study area according to the Mann-Kendall test and in 57.85%, 68.38% and 85.29% according to the correlation analysis method. However, the change trends were not significant, the significant trends at the 95% confidence level only accounted for a small proportion. Analysis of NDVI a , NPP and RUE series showed a significant decreasing trend in 9.21%, 4.81% and 6.51% with the Mann-Kendall test. The NPP change trends showed obvious positive link with the precipitation in the study area. While the effect of the inter-annual variation of the precipitation for RUE was small, the vegetation RUE can provide valuable insights into the status of land condition and had best sensitivity to land degradation

Synchronism of runoff response to climate change in Kaidu River Basin in Xinjiang, Northwest China

Institute of Scientific and Technical Information of China (English)

Jie Xue; JiaQiang Lei; DongWei Gui; JianPing Zhao; DongLei Mao; Jie Zhou

2016-01-01

The runoff in alpine river basins where the runoff is formed in nearby mountainous areas is mainly affected by temperature and precipitation. Based on observed annual mean temperature, annual precipitation, and runoff time-series datasets during 1958–2012 within the Kaidu River Basin, the synchronism of runoff response to climate change was analyzed and iden-tified by applying several classic methods, including standardization methods, Kendall's W test, the sequential version of the Mann-Kendall test, wavelet power spectrum analysis, and the rescaled range (R/S) approach. The concordance of the nonlinear trend variations of the annual mean temperature, annual precipitation, and runoff was tested significantly at the 0.05 level by Kendall's W method. The sequential version of the Mann-Kendall test revealed that abrupt changes in annual runoff were synchronous with those of annual mean temperature. The periodic characteristics of annual runoff were mainly consistent with annual precipitation, having synchronous 3-year significant periods and the same 6-year, 10-year, and 38-year quasi-periodicities. While the periodic characteristics of annual runoff in the Kaidu River Basin tracked well with those of annual precipitation, the abrupt changes in annual runoff were synchronous with the annual mean temperature, which directly drives glacier- and snow-melt processes. R/S analysis indicated that the annual mean temperature, annual precipitation, and runoff will continue to increase and remain synchronously persistent in the future. This work can im-prove the understanding of runoff response to regional climate change to provide a viable reference in the management of water resources in the Kaidu River Basin, a regional sustainable socio-economic development.

Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

Directory of Open Access Journals (Sweden)

Zhanchao Li

2013-01-01

Full Text Available The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model and change of sequence distribution law of nonparametric statistical model. On this basis, through the reduction of change point problem, the establishment of basic nonparametric change point model, and asymptotic analysis on test method of basic change point problem, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is created in consideration of the situation that in practice concrete dam crack behavior may have more abnormality points. And the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is used in the actual project, demonstrating the effectiveness and scientific reasonableness of the method established. Meanwhile, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality has a complete theoretical basis and strong practicality with a broad application prospect in actual project.

Nonparametric correlation models for portfolio allocation

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Casas, Isabel

2013-01-01

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....

Nonparametric regression using the concept of minimum energy

International Nuclear Information System (INIS)

Williams, Mike

2011-01-01

It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

Testing and Estimating Shape-Constrained Nonparametric Density and Regression in the Presence of Measurement Error

KAUST Repository

Carroll, Raymond J.

2011-03-01

In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.

Bayesian nonparametric system reliability using sets of priors

NARCIS (Netherlands)

Walter, G.M.; Aslett, L.J.M.; Coolen, F.P.A.

2016-01-01

An imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through bounds on the functioning probability. Given component level test

Dry spell, onset and cessation of the wet season rainfall in the Upper Baro-Akobo Basin, Ethiopia

Science.gov (United States)

Kebede, Asfaw; Diekkrüger, Bernd; Edossa, Desalegn C.

2017-08-01

In this study, maximum dry spell length and number of dry spell periods of rainy seasons in the upper Baro-Akobo River basin which is a part of the Nile basin, Western Ethiopia, were investigated to analyse the drought trend. Daily rainfall records of the period 1972-2000 from eight rain gauge stations were used in the analysis, and Mann-Kendall test was used to test trends for significance. Furthermore, the beginning and end of the trend development in the dry spell were also tested using the sequential version of Mann-Kendall test. Results have shown that there is neither clear monotonic trend found in dry spell for the basin nor significant fluctuation in the onset, cession and duration of rainfall in the Baro-Akobo river basin. This sufficiently explains why rain-fed agriculture has suffered little in the western part of Ethiopia. The predictable nature of dry spell pattern may have allowed farmers to adjust to rainfall variability in the basin. Unlike many parts of Ethiopia, the Baro-Akobo basin climate variability is not a limiting factor for rain-fed agriculture productivity which may contribute significantly to national food security.

EVALUASI HIDDEN CURRICULUM DI SMP NEGERI BOJA, KABUPATEN KENDAL

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Neni Lestari

2015-12-01

Full Text Available This study aimed to evaluate the implementation and impact of Hidden Curriculum, as well as the determinant factors of success and sustainability in SMPN 2 Boja Kendal. This study was an evaluative research using qualitative approach. The data collected by using observation, interviews, and documentation. Data analyzed by collecting and selecting to be deduce. Validity used triangulation data that combined the result of observation, interviews, and documentation. The results of the study were: 1 The activities of hidden curriculum development at SMPN 2 Boja Kendal, namely: flag ceremony, school environmental management, establishing and enforcing discipline, special religious worship, smiles, greetings and courtesies, exemplary, relationship among students and principal, teachers, and staff, school canteen services. 2 The impact of the hidden curriculum development was the changing of school community’s behavior being better, created clean and beautiful school environment, the improvement of public trust to the school toward their kids’ education. Development of the hidden curriculum could establish students good character and an optimal achievement as well as a good school culture. 3 Internal supporting factors including: qualified human resources, the availability of school facilities, school environment was clean and beautiful. External supporting factors occur in the form of endorsement of the parents, school committees and communities in establishing good and virtuous character for the students.

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

Manne Siegbahn and the 1924 Nobel Prize for Physics

International Nuclear Information System (INIS)

Bergstroem, I.

1988-01-01

The Research Institute of Physics celebrates its fiftieth anniversary with a Workshop and Symposium on the Physics of Low-Energy Stored and Trapped Particles. On July 1, 1937, Professor Manne Siegbahn was appointed the first director of the Institute. Because of this celebration a personal account is given of Manne Siegbahn's contribution to atomic structure physics. Comments will also be given on the procedure in the Swedish Academy of Sciences when Siegbahn in 1925 received the 1924 Nobel Prize for Physics 'for his discoveries and research in the field of X-ray spectroscopy'. (orig.)

Analysis of reference evapotranspiration (ET0) trends under climate change in Bangladesh using observed and CMIP5 data sets

Science.gov (United States)

Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid; Ongoma, Victor

2018-03-01

ET0 is an important hydro-meteorological phenomenon, which is influenced by changing climate like other climatic parameters. This study investigates the present and future trends of ET0 in Bangladesh using 39 years' historical and downscaled CMIP5 daily climatic data for the twenty-first century. Statistical Downscaling Model (SDSM) was used to downscale the climate data required to calculate ET0. Penman-Monteith formula was applied in ET0 calculation for both the historical and modelled data. To analyse ET0 trends and trend changing patterns, modified Mann-Kendall and Sequential Mann-Kendall tests were, respectively, done. Spatial variations of ET0 trends are presented by inverse distance weighting interpolation using ArcGIS 10.2.2. Results show that RCP8.5 (2061-2099) will experience the highest amount of ET0 totals in comparison to the historical and all other scenarios in the same time span of 39 years. Though significant positive trends were observed in the mid and last months of year from month-wise trend analysis of representative concentration pathways, significant negative trends were also found for some months using historical data in similar analysis. From long-term annual trend analysis, it was found that major part of the country represents decreasing trends using historical data, but increasing trends were observed for modelled data. Theil-Sen estimations of ET0 trends in the study depict a good consistency with the Mann-Kendall test results. The findings of the study would contribute in irrigation water management and planning of the country and also in furthering the climate change study using modelled data in the context of Bangladesh.

Hubungan antara Riwayat Paparan Asap Rokok dengan Kejadian Ketuban Pecah Dini pada Ibu Hamil di RSUD Dr. H. Soewondo Kendal

Directory of Open Access Journals (Sweden)

Muntoha Muntoha

2013-12-01

Full Text Available Background : The incidence of maternal mortality were caused by bleeding, eclampsia, bleeding before labor and infection. One of the triggering factors caused the onset of infection was premature rupture (PR. It defined as the rupture of amniotic membrane without uterus contractions and labor signs. The strength of amniotic membrane could also be disrupted due to the effect of nicotine of cigarette. The nicotine contained in cigarette was harmful to the pregnancies. The premature rupture rate in Indonesia was quite high. In Kendal regency the number of pregnant women who experienced in premature rupture in the year 2011 was approximately 445 patients. Meanwhile, in January up to September 2012 the premature rupture cases reached about 542 patients. Based on the preliminary survey conducted on 7 premature rupture patients in dr.H.Soewondo hospital Kendal in October 2012 the data obtained 5 (71,4% patients had a history of smoking husbands. Methode : This study purposed to know the most influential variable to the incidents of premature rupture in pregnant women in dr.H.Soewondo Kendal, Central Java Province. The design of the study used case control. The case population was pregnant women with premature rupture. Meanwhile, the control population of normal pregnant women and the sampling technique used accidental sampling. The collecting data used questionnaire, checklist and tool, rapid diagnostic cotinine test. The data analysis used chi square test. Result : The result of the study showed the most influential variable to the incidents of premature rupture was the history of cigarette smoke exposure with value p = 0,00 and OR 23,188. Thus, it could be concluded that the history of cigarette smoke exposure was the most influential variable to the incidents of the premature rupture than parity and polyhidramnion history. Keywords  : the cigarette smoke exposure, premature rupture, cotinine, polyhidramnion.

Nonparametric Bayesian Modeling of Complex Networks

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Mørup, Morten

2013-01-01

an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

Science.gov (United States)

Sharma, Priyank J.; Loliyana, V. D.; S. R., Resmi; Timbadiya, P. V.; Patel, P. L.

2017-12-01

The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944-2013) and temperature (1969-2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen's slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up

Pembukuan dalam Menunjang Kesuksesan Usaha Pengrajin Batik di Kecamatan Cepiring Kabupaten Kendal

Directory of Open Access Journals (Sweden)

Aprih Santoso

2017-09-01

Full Text Available Kecamatan Cepiring merupakan satu dari 20 kecamatan di Kabupaten Kendal dengan mata pencaharian penduduk Kecamatan Cepiring sebagian besar ada di sektor pertanian, urutan kedua dan ketiga adalah sektor industri pengolahan dan sektor perdagangan, hotel dan restoran. Usaha Kecil Mikro (UKM pengrajin Batik di Kecamatan Cepiring berjumlah 30 orang. UKM pengrajin Batik di Kecamatan Cepiring ternyata masih banyak pula dijumpai kendala diantaranya adalah: (1 belum tersusunnya strategi pengembangan usaha dan data base profile masing-masing UKM pengrajin Batik di Kecamatan Cepiring; (2 belum adanya kejelasan tentang manajemen sistem pembukuan/akuntansi secara baik dan benar sehingga menghasilkan informasi keuangan yang bermanfaat untuk pendukung UKM pengrajin Batik di Kecamatan Cepiring. Kegiatan penyuluhan pembukuan/akuntansi secara baik dan benar sehingga menghasilkan informasi keuangan yang bermanfaat untuk pendukung UKM pengrajin Batik di Kecamatan Cepiring. Penelitian ini menemukan bahwa hasil penyuluhan pembukuan dalam menunjang kesuksesan usaha pengrajin batik di Kecamatan Cepiring Kabupaten Kendal telah terlaksana dengan sukses. Hal ini terbukti dengan antusiasnya peserta penyuluhan mengikuti dan berdiskusi (termasuk proses tanya jawab dengan rutin.

Manne Siegbahn and the 1924 Nobel Prize for Physics

Energy Technology Data Exchange (ETDEWEB)

Bergstroem, I.

1988-01-01

The Research Institute of Physics celebrates its fiftieth anniversary with a Workshop and Symposium on the Physics of Low-Energy Stored and Trapped Particles. On July 1, 1937, Professor Manne Siegbahn was appointed the first director of the Institute. Because of this celebration a personal account is given of Manne Siegbahn's contribution to atomic structure physics. Comments will also be given on the procedure in the Swedish Academy of Sciences when Siegbahn in 1925 received the 1924 Nobel Prize for Physics 'for his discoveries and research in the field of X-ray spectroscopy'.

PERAN GURU PENJASORKES DALAM MENGATASI KENAKALAN SISWA (STUDI KASUS DI SMA NEGERI SE-KABUPATEN KENDAL TAHUN 2013

Directory of Open Access Journals (Sweden)

Irkham Kharisma

2015-06-01

Full Text Available The purpose of this study to determine, describe, and analyze the role of teachers in addressing student misbehavior penjasorkes Public High School students in Kendal. This study used qualitative methods, the location of the research conducted in SMA se-Kendal. Research subjects in this study were penjasorkes teacher, principal, BK teachers and students. Data collected by using observation, interviews and documentation. The validity of using triangulation source. Data analysis using descriptive analysis model according to Miles and Huberman. Based on the results of research conducted and has been linked with the theory Suparwoto, et al. It can be concluded that the role of teachers penjasorkes (1 in terms of preventive prevent student misbehavior is good. (2 is good in terms of repression. (3 in terms of curative and rehabilitation are good. The conclusions that can be drawn from this research is the teacher's role in addressing delinquency penjasorkes students in SMA se-Kendal has been running both in terms of preventive, repressive and curative or rehabilitation.

Nonparametric Bayes Modeling of Multivariate Categorical Data.

Science.gov (United States)

Dunson, David B; Xing, Chuanhua

2012-01-01

Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.

Multivariate nonparametric regression and visualization with R and applications to finance

CERN Document Server

Klemelä, Jussi

2014-01-01

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functio

Decision support using nonparametric statistics

CERN Document Server

Beatty, Warren

2018-01-01

This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.

PENGARUH MOTIVASI BELAJAR, DISIPLIN BELAJAR DAN MEDIA PEMBELAJARAN TERHADAP KESIAPAN BELAJAR SISWA KELAS X ADMINISTRASI PERKANTORAN PADA MATA DIKLAT MENGELOLA PERALATAN KANTOR DI SMK NU 01 KENDAL

Directory of Open Access Journals (Sweden)

Ayu Fitria Yanida, Hengky Pramusinto

2014-11-01

Full Text Available Tujuan penelitian ini adalah untuk mengetahui Pengaruh motivasi belajar, disiplin belajar dan media pembelajaran terhadap kesiapan belajar siswa kelas X administrasi perkantoran pada mata diklat mengelola peralatan kantor di SMK NU 01 Kendal baik secara simultan maupun parsial.Populasi dalam penelitian ini adalah siswa kelas X jurusan administrasi perkantoran sebanyak 94siswa.Metode pengumpulan data yang digunakan adalah metode kuesioner dan dokumentasi.Teknik analisis data menggunakan analisis deskriptif persentase, analisis regresi linier berganda, analisis uji asumsi klasik, dan analisis uji hipotesis.Analisis regresi berganda menunjukkan bahwa ada pengaruh motivasi belajar, disiplin belajar dan media pembelajaran terhadap kesiapan belajar siswa kelas X administrasi perkantoran pada mata diklat mengelola peralatan kantor di SMK NU 01 Kendal baik secara simultan maupun parsial. Preparation to studyis the basic need that must be done by students Office Equipment learning outcomes. Learning readiness can be influenced by learning motivation, learning discipline and learning media. The problem of this study:Was there are any influence of learning motivation, learning discipline and learning media toward the 10th grade students’ learning readiness of OfficeAdministration in managing Office Equipment in SMK NU 01 Kendal. The population were 10thgrade student of Office Administration at SMK NU 01 Kendal, they were 94 students. The data were collected by questiononaires and documentation. The data were analyzed by percentage desciptive analiysis, multiple linear regression analysis, analysis classical assumption test, hypothesis testing and SPSS analysis. The results of multiple linear regression analysis showed that the equation Y = 7.472 + 0.163X1 + 0.155X2+ 0.369X3, with F test was obtained F = 16.278 with a significance 0.000 and less than 0.05. Simultaneously, the influence of learning motivation, learning discipline and learning media toward

Spatial and temporal variability of fluoride concentrations in groundwater resources of Larestan and Gerash regions in Iran from 2003 to 2010.

Science.gov (United States)

Amini, Hassan; Haghighat, Gholam Ali; Yunesian, Masud; Nabizadeh, Ramin; Mahvi, Amir Hossein; Dehghani, Mohammad Hadi; Davani, Rahim; Aminian, Abd-Rasool; Shamsipour, Mansour; Hassanzadeh, Naser; Faramarzi, Hossein; Mesdaghinia, Alireza

2016-02-01

There is discrepancy about intervals of fluoride monitoring in groundwater resources by Iranian authorities. Spatial and temporal variability of fluoride in groundwater resources of Larestan and Gerash regions in Iran were analyzed from 2003 to 2010 using a geospatial information system and the Mann-Kendall trend test. The mean concentrations of fluoride for the 8-year period in the eight cities and 31 villages were 1.6 and 2.0 mg/l, respectively; the maximum values were 2.4 and 3.8 mg/l, respectively. Spatial, temporal, and spatiotemporal variability of fluoride in overall groundwater resources were relatively constant over the years. However, results of the Mann-Kendall trend test revealed a monotonic trend in the time series of one city and 11 villages for the 8-year period. Specifically, one city and three villages showed positive significant Kendall's Tau values, suggesting an upward trend in fluoride concentrations over the 8-year period. In contrast, seven villages displayed negative significant Kendall's Tau values, arguing for a downward trend in fluoride concentrations over the years. From 2003 to 2010, approximately 52 % of the Larestan and Gerash areas have had fluoride concentrations above the maximum permissible Iranian drinking water standard fluoride level (1.4 mg/l), and about 116,000 people were exposed to such excess amounts. Therefore, our study supports for a close monitoring of fluoride concentrations from health authorities in monthly intervals, especially in villages and cities that showed positive trend in fluoride concentrations. Moreover, we recommend simultaneous implementation of cost-effective protective measures or interventions until a standard fluoride level is achieved.

PENGARUH STRUKTUR MODAL DAN VOLUME PENJUALAN TERHADAP PROFITABILITAS PADA PRIMER KOPERASI PURNAWIRAWAN ANGKATAN BERSENJATA REPUBLIK INDONESIA (PRIMKOPPABRI DI KABUPATEN KENDAL PERIODE 2010-2012

Directory of Open Access Journals (Sweden)

Masumi Ananingati Rahayu

2014-02-01

Full Text Available Tujuan penelitian ini adalah untuk mengetahui dan menganalisis pengaruh secara parsial maupun simultan struktur modal dan volume penjualan terhadap profitabilitas pada Primer Koperasi Purnawirawan Angkatan Bersenjata Republik Indonesia(PRIMKOPPABRI di Kabupaten Kendal. Penelitian ini menggunakan pendekatan kuantitatif dan jenis penelitian deskriptif dengan menggunakan motede statistik dan bersifat kausalitas yang mengacu pada laporan keuangan (neraca dan rugi laba dalam bentuk bulanan periode Januari sampai Desember selama tahun 2010-2012. Berdasarkan hasil uji secara parsial untuk struktur modal dan volume penjualan terhadap profitabilitas berpengaruh secara signifikan dengan kontribusi sebesar 14,5% untuk struktur modal sedangkan volume penjualan sebesar 7,07%. Secara simultan ada pengaruh yang signifikan antara struktur modal dan volume penjualan terhadap profitabilitas pada PRIMKOPPABRI Kab.Kendal dengan kontribusi sebesar 18,5%. Dari hasil perhitungan diperoleh persamaan regresi berganda sebagai berikut: Y= -0,005 + 0,029 X1+ 0,019 X 2 + e. The purpose of this study is to investigate and analyze the effect of partially and simultaneously the capital structure on profitability and sales volume in the Primary Cooperative Retired Armed Forces of the Republic of Indonesia (PRIMKOPPABRI in Kendal. This study used a quantitative approach and descriptive research using statistical motede and causality are referring to the financial statements (balance sheet and income statement in the form of a monthly period of January to December during the years 2010-2012. Based on the test results for the partial capital structure on profitability and sales volume of significant influence with a contribution of 14,5 % to the capital structure while sales volume amounted to 7,07%. Simultaneously there is a significant influence of capital structure on profitability and sales volume in PRIMKOPPABRI Kab.Kendal with a contribution of 18,5 %. From the calculations

Thomas Mann's Death in Venice or Plutarch's way towards Eros

OpenAIRE

Gilabert Barberà, Pau

2010-01-01

In Death in Venice Thomas Mann refers explicitly to Plato's Symposium and Phaedrus in order to explain the relationship between Gustav von Aschenbach and Tadzio but he hides that his novel also depends on Plutarch's Eroticus. Why? The aim of this article is precisely to reveal the different reasons for such an attitude. Indeed, Plutarch speaks highly of conjugal love in his Eroticus and this way is not followed by Mann in Death in Venice but, at the same, the German writer finds in this Pluta...

Drought trends indicated by evapotranspiration deficit over the contiguous United States during 1896-2013

Science.gov (United States)

Kim, Daeha; Rhee, Jinyoung

2016-04-01

Evapotranspiration (ET) has received a great attention in drought assessment as it is closely related to atmospheric water demand. The hypothetical potential ET (ETp) has been predominantly used, nonetheless it does not actually exist in the hydrologic cycle. In this work, we used a complementary method for ET estimation to obtain wet-environment ET (ETw) and actual ET (ETa) from routinely observed climatic data. By combining ET deficits (ETw minus ETa) and the structure of the Standardized Precipitation-Evapotranspiration Index (SPEI), we proposed a novel ET-based drought index, the Standardized Evapotranspiration Deficit Index (SEDI). We carried out historical drought identification for the contiguous United States using temperature datasets of the PRISM Climate Group. SEDI presented spatial distributions of drought areas similar to the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) for major drought events. It indicates that SEDI can be used for validating other drought indices. Using the non-parametric Mann-Kendall test, we found a significant decreasing trend of SEDI (increasing drought risk) similar to PDSI and SPI in the western United States. This study suggests a potential of ET-based indices for drought quantification even with no involvement of precipitation data.

Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

Science.gov (United States)

Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

2015-12-01

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

Trends and variability in the hydrological regime of the Mackenzie River Basin

Science.gov (United States)

Abdul Aziz, Omar I.; Burn, Donald H.

2006-03-01

Trends and variability in the hydrological regime were analyzed for the Mackenzie River Basin in northern Canada. The procedure utilized the Mann-Kendall non-parametric test to detect trends, the Trend Free Pre-Whitening (TFPW) approach for correcting time-series data for autocorrelation and a bootstrap resampling method to account for the cross-correlation structure of the data. A total of 19 hydrological and six meteorological variables were selected for the study. Analysis was conducted on hydrological data from a network of 54 hydrometric stations and meteorological data from a network of 10 stations. The results indicated that several hydrological variables exhibit a greater number of significant trends than are expected to occur by chance. Noteworthy were strong increasing trends over the winter month flows of December to April as well as in the annual minimum flow and weak decreasing trends in the early summer and late fall flows as well as in the annual mean flow. An earlier onset of the spring freshet is noted over the basin. The results are expected to assist water resources managers and policy makers in making better planning decisions in the Mackenzie River Basin.

Comparação de duas metodologias de amostragem atmosférica com ferramenta estatística não paramétrica Comparison of two atmospheric sampling methodologies with non-parametric statistical tools

Directory of Open Access Journals (Sweden)

Maria João Nunes

2005-03-01

Full Text Available In atmospheric aerosol sampling, it is inevitable that the air that carries particles is in motion, as a result of both externally driven wind and the sucking action of the sampler itself. High or low air flow sampling speeds may lead to significant particle size bias. The objective of this work is the validation of measurements enabling the comparison of species concentration from both air flow sampling techniques. The presence of several outliers and increase of residuals with concentration becomes obvious, requiring non-parametric methods, recommended for the handling of data which may not be normally distributed. This way, conversion factors are obtained for each of the various species under study using Kendall regression.

Change-Point and Trend Analysis on Annual Maximum Discharge in Continental United States

Science.gov (United States)

Serinaldi, F.; Villarini, G.; Smith, J. A.; Krajewski, W. F.

2008-12-01

Annual maximum discharge records from 36 stations representing different hydro-climatic regimes in the continental United States with at least 100 years of records are used to investigate the presence of temporal trends and abrupt changes in mean and variance. Change point analysis is performed by means of two non- parametric (Pettitt and CUSUM), one semi-parametric (Guan), and two parametric (Rodionov and Bayesian Change Point) tests. Two non-parametric (Mann-Kendall and Spearman) and one parametric (Pearson) tests are applied to detect the presence of temporal trends. Generalized Additive Model for Location Scale and Shape (GAMLSS) models are also used to parametrically model the streamflow data exploiting their flexibility to account for changes and temporal trends in the parameters of distribution functions. Additionally, serial correlation is assessed in advance by computing the autocorrelation function (ACF), and the Hurst parameter is estimated using two estimators (aggregated variance and differenced variance methods) to investigate the presence of long range dependence. The results of this study indicate lack of long range dependence in the maximum streamflow series. At some stations the authors found a statistically significant change point in the mean and/or variance, while in general they detected no statistically significant temporal trends.

PENGARUH HASIL BELAJAR MATA PELAJARAN PRODUKTIF AKUNTANSI, PROGRAM PRAKTIK KERJA INDUSTRI DAN SELF EFFICACY TERHADAP KESIAPAN KERJA SISWA KELAS XII PROGRAM KEAHLIAN AKUNTANSI DI SMK NEGERI 1 KENDAL TAHUN AJARAN 2013/2014

Directory of Open Access Journals (Sweden)

Noviana Noviana

2013-02-01

Academic Year 2013/2014 either partial or simultan. The study type is causalitas test use quantitative approach. The study population was all students of class XII accounting skills program a number of 105 students. In this study, the data collection method used is the method of documentation and questionnaire method / questionnaire. The methods of data analysis using descriptive analysis, multiple regression analysis, testing the coefficient of determination (R2, simultan test (F, and test individual parameter (t. The results of this study in partial test are influence learning outcomes productive subjects accounting for 25,70 %, on the job trainning program for 23,20 %, and 32,90 % of self-efficacy on job readiness class XII students. While in simultan are influence learning outcomes productive subjects accounting, on the job trainning program, and self-efficacy toward job readiness class XII students accounting skills program at SMK Negeri 1 Kendal school year 2013/2014 as 43,10%.

Nonparametric Transfer Function Models

Science.gov (United States)

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Bayesian nonparametric data analysis

CERN Document Server

Müller, Peter; Jara, Alejandro; Hanson, Tim

2015-01-01

This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.

FAKTOR-FAKTOR YANG MEMPENGARUHI KESULITAN BELAJAR IPS TERPADU KELAS VII DI SMP NEGERI 1 PLANTUNGAN KABUPATEN KENDAL

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Lina Maftukhah,

2012-10-01

. Berdasarkan hasil penelitian, diharapkan guru sebaiknya memberi latihan-latihan dan tugas-tugas untuk mengasah kemampuan siswa. Untuk siswa sebaiknya membentuk kelompok belajar, serta untuk orang tua selalu memberikan dukungan yang penuh terhadap putra-putrinya dalam belajar sehingga siswa dapat belajar dengan maksimal. Learning difficulties are influenced by such kind of factors whether it is the intern or extern factors. Based on the observation result from the data of Integrated Social Science final examination, most of the seven grade students in SMP Negeri 1 Plantungan got the low marks and they could not pass the KKM. It can indicate that students have the learning difficulties in Integrated Social Science subject.The problemsthat were examinedin this studyare whatare the factorsthat influencelearning difficultiesof IntegratedSocial Scienceand whatis more dominant factor affectingthe Integrated Social Science learning difficulties for Seventh Grade Studentsof SMP Negeri 1 Plantungan, Kendal School Year 2011/2012. This studyaims to determinethe factors that influence learning difficulties of Integrated Social Science and the more dominant factor of it. The research was conductedat SMP Negeri 1 Plantungan, Kendal. The population was 131 seven grade students. Sampling wasdone by using claster proportiona lrandom sampling and obtained 100 samplesof students.The variablesin this studyare the factorst hat influence learning difficulties of Integrated Social Science in seven grade of SMP Negeri 1 Plantungan, Kendal. Data collection methodswere questionnaires and documentation methods. Then, the data was analyzed by the factor analysis and percentage descriptive. Based onfactor analysis, there are 5 components thatwill form 5 new factors. The students learning difficulties level from 5 new factors based on the test of percentage descriptionas follows: (a 61.55% the students ability, (b 66.75% teachers' ability, (c 77.00% supporting media, (d 72.67% school support, (e 62

Using non-parametric methods in econometric production analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

2012-01-01

by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...

Another proof of Gell-Mann and Low's theorem

OpenAIRE

Molinari, Luca Guido

2006-01-01

The theorem by Gell-Mann and Low is a cornerstone in QFT and zero-temperature many-body theory. The standard proof is based on Dyson's time-ordered expansion of the propagator; a proof based on exact identities for the time-propagator is here given.

A Tribute to Manne Siegbahn

Science.gov (United States)

Kubbinga, Henk

2017-11-01

Spectroscopy came to dominate the 19th century, with a crucial role for Swedish physicists. It was Anders Ångström who introduced the tenmillionth part of a millimeter as the wavelength unit (1868), a unit that was adopted by Rowland for his tables of the solar spectral lines (1887-1893). Janne Rydberg, then, followed in Ångström's footsteps in searching for relations between the emission spectra of the elements and their place in the Periodic Table. Röntgen's new rays became a next challenge, demanding a form of spectroscopy of their own. Manne Siegbahn, an assistant of Rydberg, then, devised appropriate instruments of ever increasing precision.

Spatial and Temporal Streamflow Trends in Northern Taiwan

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Chen-Feng Yeh

2015-02-01

Full Text Available Streamflow is an important factor in the study of water resource management, floods, and droughts. Dramatic climate change has created extreme rainfall distributions, making the study of streamflow trends and variability even more crucial. In this study, the long-term streamflow data and trends recorded at gauging stations in Northern Taiwan are analyzed using the Mann-Kendall test. The data used for trend analysis are the average annual streamflow, the average seasonal streamflow, and the high and low flows. The slope trend is calculated using the Theil-Sen estimator. Finally, change point analysis is conducted using the Mann-Whitney-Pettit test and the cumulative deviation test to gain further information about the change points and to understand the changes in streamflow before and after the change points. The average annual streamflow of the 12 gauging stations in the study area is analyzed using the Mann-Kendall test. The results show that of the 12 gauging stations, only the Ximen Bridge Station in the Lanyang River basin show a significant downward streamflow trend. Results of the monthly and seasonal average streamflow analysis show that in the spring, 72.2% of the gauging stations showed upward streamflow trends, most of which were located in the Tamsui River and the Touqian River basins. The high and low flow data analysis shows that the Ximen Bridge Station was the only gauging station to feature a significant downward streamflow trend for both high and low flows. This distribution pattern provides valuable information for regional hydrological studies and water management.

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Science.gov (United States)

Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

2011-05-01

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

Multiyear Rainfall and Temperature Trends in the Volta River Basin and their Potential Impact on Hydropower Generation in Ghana

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Amos T. Kabo-Bah

2016-10-01

Full Text Available The effects of temperature and rainfall changes on hydropower generation in Ghana from 1960–2011 were examined to understand country-wide trends of climate variability. Moreover, the discharge and the water level trends for the Akosombo reservoir from 1965–2014 were examined using the Mann-Kendall test statistic to assess localised changes. The annual temperature trend was positive while rainfall showed both negative and positive trends in different parts of the country. However, these trends were not statistically significant in the study regions in 1960 to 2011. Rainfall was not evenly distributed throughout the years, with the highest rainfall recorded between 1960 and 1970 and the lowest rainfalls between 2000 and 2011. The Mann-Kendall test shows an upward trend for the discharge of the Akosombo reservoir and a downward trend for the water level. However, the discharge irregularities of the reservoir do not necessarily affect the energy generated from the Akosombo plant, but rather the regular low flow of water into the reservoir affected power generation. This is the major concern for the operations of the Akosombo hydropower plant for energy generation in Ghana.

Another proof of Gell-Mann and Low's theorem

International Nuclear Information System (INIS)

Molinari, Luca Guido

2007-01-01

The theorem by Gell-Mann and Low is a cornerstone in quantum field theory and zero-temperature many-body theory. The standard proof is based on Dyson's time-ordered expansion of the propagator; a proof based on exact identities for the time propagator is here given

kruX: matrix-based non-parametric eQTL discovery.

Science.gov (United States)

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Application of nonparametric statistics to material strength/reliability assessment

International Nuclear Information System (INIS)

Arai, Taketoshi

1992-01-01

An advanced material technology requires data base on a wide variety of material behavior which need to be established experimentally. It may often happen that experiments are practically limited in terms of reproducibility or a range of test parameters. Statistical methods can be applied to understanding uncertainties in such a quantitative manner as required from the reliability point of view. Statistical assessment involves determinations of a most probable value and the maximum and/or minimum value as one-sided or two-sided confidence limit. A scatter of test data can be approximated by a theoretical distribution only if the goodness of fit satisfies a test criterion. Alternatively, nonparametric statistics (NPS) or distribution-free statistics can be applied. Mathematical procedures by NPS are well established for dealing with most reliability problems. They handle only order statistics of a sample. Mathematical formulas and some applications to engineering assessments are described. They include confidence limits of median, population coverage of sample, required minimum number of a sample, and confidence limits of fracture probability. These applications demonstrate that a nonparametric statistical estimation is useful in logical decision making in the case a large uncertainty exists. (author)

Impact of climate change on potential evapotranspiration (case study: west and NW of Iran)

Science.gov (United States)

Dinpashoh, Y.; Jahanbakhsh-Asl, S.; Rasouli, A. A.; Foroughi, M.; Singh, V. P.

2018-04-01

Potential evapotranspiration (ET0) is one of the main elements when computing agricultural irrigation requirements and scheduling. All climatic parameters as well as ET0 are influenced by climate change. The aim of this study is trend analysis of monthly and annual ET0 time series in the west and NW of Iran. Values of ET0 are estimated at 36 selected stations, using the FAO-56 Penman-Monteith (FAO-56 PM) method. Then, the non-parametric Mann-Kendall (MK) method was used to detect trends. The slopes of trend lines are estimated using Sen's estimator approach. Results showed that about 86%of the monthly ET0 time series had upward trends of which 35.6 and 43% were significant at 0.01 and 0.05 levels, respectively, 47.4% exhibited a significant upward trend at the 10% level. In contrast, less than 0.7% of the whole monthly ET0 time series showed a significant downward trend (α water in a prudent manner in this area.

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

Science.gov (United States)

Du, Pang; Tang, Liansheng

2009-01-30

When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

Nonparametric statistics a step-by-step approach

CERN Document Server

Corder, Gregory W

2014-01-01

"…a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.  It also deserves a place in libraries of all institutions where introductory statistics courses are taught."" -CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical powerSPSS® (Version 21) software and updated screen ca

The Effect of Weaning Food on the Body Weight of 6-12 Months Infants in Posyandu Kutoharjo Village, Kaliwungu, Kendal

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Nur Nahdloh

2013-12-01

Full Text Available According to Central Java Riskesdas in 2007 the severe malnutrition rate was 4.0%, while the rate in Kendal district was 3.1%. The age of 6-12 months is important because it is transition from liquid to solid foods. A purely breast milk diet is unsufficient to meet the nutritional needs of a fast growing baby growth. Weaning diet for baby is necessary to prevent growth disorder. The aim of the study was to assess the effect of weaning diet on weight gain of 6-12 month infant in posyandu (intergrated health center of Kutoharjo Kaliwungu Kendal. The study was an analytic observational study with a cross sectional design. 87 samples were taken from the visits of children aged 6-12 months in the posyandu consisted of 53 boys and 34 girls who met the inclusion and exclusion criteria. The informations of weaning diet was obtained by questionare and interview. The results classified the baby into two groups namely the appropiate groups and inappropriate groups. The infant’s growth was assessed using the growth chart for the previous two months. Data were analyzed by Chi-Square Test. 51 (58.6% infants fed of the appropriate solid foods, 44 (50.6% had a good weight gain growth and only 7 (8% infants has a bad weight gain. While of 36 (41.4% infants fed inappropriate weaning diet, 30 (34.5% infants had a bad weight gain and only 6 (6.9% infants had a good weight gain. The Chi-Square analysis showed p-value of 0.000 (p<0.05, which means that there was a significant difference between the two groups. The weaning food affect on weight gain of 6-12 month infants in posyandu Kutoharjo village Kaliwungu Kendal.

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

Science.gov (United States)

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

A nonparametric mixture model for cure rate estimation.

Science.gov (United States)

Peng, Y; Dear, K B

2000-03-01

Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

A Bayesian Beta-Mixture Model for Nonparametric IRT (BBM-IRT)

Science.gov (United States)

Arenson, Ethan A.; Karabatsos, George

2017-01-01

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

A Structural Labor Supply Model with Nonparametric Preferences

NARCIS (Netherlands)

van Soest, A.H.O.; Das, J.W.M.; Gong, X.

2000-01-01

Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis.This paper presents an example where nonparametric flexibility can be attained

The reason behind the Gell-Mann-Okubo mass formula

International Nuclear Information System (INIS)

Souza, Mario Everaldo de

1994-01-01

The Gell-Mann-Okubo mass formula has been widely used as a phenomenological tool in particle physics but the underlying basis for it has not been known. This paper reveals its basis and generalizes the formula to SU(n) (n = 3,4,5,6). (author)

Nonparametric Bayesian inference for multidimensional compound Poisson processes

NARCIS (Netherlands)

Gugushvili, S.; van der Meulen, F.; Spreij, P.

2015-01-01

Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,

A note on Nonparametric Confidence Interval for a Shift Parameter ...

African Journals Online (AJOL)

The method is illustrated using the Cauchy distribution as a location model. The kernel-based method is found to have a shorter interval for the shift parameter between two Cauchy distributions than the one based on the Mann-Whitney test statistic. Keywords: Best Asymptotic Normal; Cauchy distribution; Kernel estimates; ...

Thomas Mann e a cena intelectual no Brasil: encontros e desencontros

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Sibele Paulino

2009-12-01

Full Text Available A origem brasileira de Thomas Mann, por parte de sua mãe, Julia da Silva Bruhns, deu ocasião, na maturidade do escritor, a seu contato com intelectuais brasileiros ou estrangeiros ligados à cena cultural do Brasil. No primeiro grupo, tem-se Gilberto Freyre, Sérgio Buarque de Holanda e Erico Verissimo. Residentes no Brasil, Karl Lustig-Prean, que posteriormente retornará à Europa, e o tradutor Herbert Caro, que se radica em definitivo no Brasil. Também o contato direto ou indireto com pensadores e escritores como Karl Loewenstein, Heinrich Eduard Jacob, Marte Brill e Stefan Zweig colaboraram para a aproximação de Thomas Mann ao universo brasileiro. Estes e outros pontos de contato são descritos no presente artigo, que pretende difundir dados e documentos há muito inacessíveis ou inéditos, no sentido de contribuir com abordagens atualizadas da obra de Thomas Mann e oferecer à pesquisa especializada a indicação de dados biográficos e documentais relacionados ao escritor, no que concerne à sua relação com o Brasil.

Non-parametric estimation of the individual's utility map

OpenAIRE

Noguchi, Takao; Sanborn, Adam N.; Stewart, Neil

2013-01-01

Models of risky choice have attracted much attention in behavioural economics. Previous research has repeatedly demonstrated that individuals' choices are not well explained by expected utility theory, and a number of alternative models have been examined using carefully selected sets of choice alternatives. The model performance however, can depend on which choice alternatives are being tested. Here we develop a non-parametric method for estimating the utility map over the wide range of choi...

75 FR 61479 - Kendall Head Tidal Energy Project; Notice of Preliminary Permit Application Accepted for Filing...

Science.gov (United States)

2010-10-05

... Tidal Energy Project; Notice of Preliminary Permit Application Accepted for Filing and Soliciting... Federal Power Act, proposing to study the feasibility of the Kendall Head Tidal Energy Project, located in.... The proposed project would consist of: (1) 4 OCGen\\TM\\ hydrokinetic tidal devices each consisting of...

Beberapa Faktor Yang Berhubungan Dengan Pemakaian Bahan Tambahan Pangan (BTP Pada Produk Kerupuk Di Kecamatan Kaliwungu, Kabupaten Kendal

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Zeta Rina Pujiastuti

2015-12-01

Full Text Available ABSTRACT Background : The food is a primary human necessity. In Semarang there is sold many chips, which contain a prohibited additive substances (Rhodamin B, Auramin, Metanil Yellow and Borax. Method : This is observational research using survey method. Beside that, this research also conduct laboratory examination to chips that is produced by respondent. The number of population is 50 person. They are chips producers in Kaliwungu, Kendal. The number of sample 44 persons. Result : This research showed that 43.2% chip's producers are low economic level, 65.9% chip's producer had finished elementary school / not finished elementary school / no school, 38.6% chip's producer have a low knowledge about using food additive substances. The number of respondent who have a good attitude using the food additive substance 50%. The number of respondent who have no good practice 54.5%. The result of observation to consumer showed that 40% consumers choose the colored chips. The number of chip's producer who produce the colored chips are 30 person from 44 respondents. Based on the result of questioners for the goverment (Kendal Distric Health Office, Drug and Food Control Agency in Semarang, it is known that the founding to chip's producers specifically in Kaliwungu sub district is not effectif. Key word: Food Additive Substances, Chips and Kendal

Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin.

Science.gov (United States)

Zhao, Jing; Huang, Qiang; Chang, Jianxia; Liu, Dengfeng; Huang, Shengzhi; Shi, Xiaoyu

2015-05-01

The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970. Copyright © 2015. Published by Elsevier Inc.

A q deformation of Gell-Mann-Okubo mass formula

International Nuclear Information System (INIS)

Bagchi, B.; Biswas, S.N.

1996-01-01

We explore the possibility of deforming Gell-Mann-Okubo (GMO) mass formula within the framework of a quantized enveloping algebra. A small value of the deformation parameter is found to provide a good fit to the observed mass spectra of the π, K and η, mesons. (author). 13 refs

Modelling the Effects of Land-Use Changes on Climate: a Case Study on Yamula DAM

Science.gov (United States)

Köylü, Ü.; Geymen, A.

2016-10-01

Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial's land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spatial and temporal analysis of the research area. For this research humidity, temperature, wind speed, precipitation observations which are collected in 16 weather stations nearby Kızılırmak Basin are analyzed. After that these statistical information is combined by GIS data over years. An application is developed for GIS analysis in Python Programming Language and integrated with ArcGIS software. Statistical analysis calculated in the R Project for Statistical Computing and integrated with developed application. According to the statistical analysis of extracted time series of meteorological parameters, statistical significant spatiotemporal trends are observed for climate change and land use characteristics. In this study, we indicated the effect of big dams in local climate on semi-arid Yamula Dam.

THE INFLUENCE OF EUROPEAN CLIMATE VARIABILITY MECHANISM ON AIR TEMPERATURE IN ROMANIA

Directory of Open Access Journals (Sweden)

M. MATEI

2013-03-01

Full Text Available The main objective of the present paper is to analyze the temporal and spatial variability of air-temperature in Romania, by using mean air-temperature values provided by the ECA&D project (http://eca.knmi.nl/. These data sets will be filtered by means of the EOF (Empirical Orthogonal Function analysis, which describes various modes of space variability and time coefficient series (PC series. The EOF analysis will also be used to identify the main way of action of the European climate variability mechanism, by using multiple variables in grid points, provided by the National Centre of Atmospheric Research (NCAR, USA. The variables considered here are: sea level pressure (SLP, geopotential height at 500 mb (H500 and air temperature at 850 mb (T850, for the summer and winter seasons. The linear trends and shift points of considered variables are then assessed by means of the Mann-Kendall and Pettitt non-parametric tests. By interpreting the results, we can infer that there is causal relationship between the large-scale analyzed parameters and temperature variability in Romania. These results are consistent with those presented by Busuioc et al., 2010, where the main variation trends of the principal European variables are shown.

Categorical and nonparametric data analysis choosing the best statistical technique

CERN Document Server

Nussbaum, E Michael

2014-01-01

Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain

Bayesian nonparametric hierarchical modeling.

Science.gov (United States)

Dunson, David B

2009-04-01

In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology

Directory of Open Access Journals (Sweden)

Mohamed Chikhi

2018-02-01

Full Text Available This paper analyses cyclical behaviour of Orange stock price listed in French stock exchange over 01/03/2000 to 02/02/2017 by testing the nonlinearities through a class of conditional heteroscedastic nonparametric models. The linearity and Gaussianity assumptions are rejected for Orange Stock returns and informational shocks have transitory effects on returns and volatility. The forecasting results show that Orange stock prices are short-term predictable and nonparametric NAR-ARCH model has better performance over parametric MA-APARCH model for short horizons. Plus, the estimates of this model are also better comparing to the predictions of the random walk model. This finding provides evidence for weak form of inefficiency in Paris stock market with limited rationality, thus it emerges arbitrage opportunities.

The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard

and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

Determination of r Factor of Kalbach-Mann Systematics for Energy Balance

International Nuclear Information System (INIS)

Zhang Jingshang

2008-01-01

Kalbach-Mann systematics is a very useful formula to discrete the double-differential cross sections of emitted particles. However, the energy balance by using this systematics is still a task to be studied. In the form of Legendre polynomial expansion the energy balance has been proved analytically. In terms of this approach, the formula to determine the pre-equilibrium fraction r factor of Kalbach-Mann systematics has been obtained for keeping energy balance strictly. This formula could be straightforwardly applied for describing the double-differential cross sections of all projectile types in the continuum spectrum emissions. It indicates that Legendre expansion coefficient with l = 1 is the key term in the energy balance

Manne/mange - to sider af samme sag

DEFF Research Database (Denmark)

Jensen, Anette

2009-01-01

At pronominet og adjektivet mange udtales forskelligt i danske dialekter er vist ikke ukendt for de fleste danske dialektologer. Artikelen gør nærmere rede for hvordan lydformerne fordeler sig geografisk på de to hovedformer som er -ng-formen mange og -n-formen manne med varianter, og derefter ser...

Spatial and temporal variability of rainfall in the Tocantins-Araguaia hydrographic region

Directory of Open Access Journals (Sweden)

Glauber Epifanio Loureiro

2015-01-01

Full Text Available Current paper examines the space-time dynamics of yearly rainfall of the Tocantins-Araguaia Hydrographic Region (TAHR, foregrounded on rainfall volume from isohyet maps and interpolated by Kriging geo-statistical method.  Rainfall space dynamics was undertaken by the analysis of descriptive statistics, Index of Meteorological Irregularity (IMI and Variation Coefficient. Temporal dynamics was analyzed through the distribution of total annual volume precipitation for each TAHR sub-basin by the Standardized Anomaly Index, trend and magnitude test provided by Mann-Kendall and Sen Tests. Results correlated with meteorological anomalies of the Atlantic (Dipole and Pacific (ENOS Oceans show a highly heterogeneous rainfall behavior with temporal variability. Or rather, a decrease of rainfall extensiveness during years of intense meteorological anomaly with a rainfall increase south of the High Tocantins and Araguaia sub-basins and a decrease of rainfall in the Lower Tocantins sub-basin, with El Niño features. Although the Mann-Kendall test does not show statistically a significant trend for rainfall in the TAHR region, Sen’s estimator reveals a decrease in rainfall in the High Tocantins (-1.24 km³ year-1 and Araguaia (-1.13 km³ year-1 sub-basins and a rainfall increase in the Lower Tocantins sub-basin (0.53 km³ year-1 and in the TAHR region (-1.5 km³ year-1.

Variation of Runoff and Precipitation in the Hekou-Longmen Region of the Yellow River Based on Elasticity Analysis

OpenAIRE

Li, Erhui; Mu, Xingmin; Zhao, Guangju; Gao, Peng; Shao, Hongbo

2014-01-01

Precipitation is very important to the formation of runoff, and studying of runoff variation and its response to precipitation has practical significance to sustainable utilization of water resources. The study used Mann-Kendall test, anomaly accumulation method, and precipitation elasticity of runoff method to analyze the changes in the relation of precipitation and runoff and the contribution of precipitation to runoff change in the Hekou-Longmen region (from 1957 to 2010), Huangfuchuan wat...

Effects of human activities and climate variability on water resources in the Saveh plain, Iran.

Science.gov (United States)

Mohammadi Ghaleni, M; Ebrahimi, K

2015-02-01

Quantity and quality distribution of surface water and groundwater are changing under the impacts of both climate variability and human activities. The main goal of this paper is to evaluate the abovementioned impacts on the water resources in the Saveh plain, central Iran. To achieve this aim, spatial and temporal changes of the surface and groundwater quality and quantity have been analyzed, using hydrometric and meteorological data. The nonparametric Mann-Kendall test was used to identify trends and change points in the annual rainfall and runoff for the period of 1946 to 2011. In order to analyze the impacts of the Saveh Dam on runoff, the dam operation year, 1994, was considered as a change point. Mann-Kendall test results show that rainfall time series was divided into two parts, namely, 1966-1989 and 1990-2007, and averages of annual rainfall in five stations increase from 10 to 21 %. Also, runoff time series was divided into two parts, namely, 1946-1995 and 1996-2007 and averages of annual runoff in four stations decrease from 8 to 83 %. Results show that rainfall changes in Shahabasi, Razin, Jalayer, Emamabad, and Ahmadabad stations increased from 9 to 33 % before and after 1994. Nevertheless, runoff decreased from 24 to 81 %. The results indicate that the greatest lack of runoff between stations is at Shahabasi station and one important reason for the severe lack is operation of the Saveh Dam in 1994. Highest groundwater level decline, about 168.67 cm, occurred in 1994 that is the operation year of the Saveh Dam. Trend analysis of surface water quality show that electrical conductivity increased 957.34 μmho/cm before and after 1994. Also, the Wilcox water quality classification method has been reduced from C3-S1 to C4-S2. Average groundwater electrical conductivity (EC) during 1999-2003 and 2004-2009 increased to 89.6 μmho/cm. Also, the groundwater quality indices for agricultural usages are classified in four classes including, C4-S2 16, C4-S1 46, C3-S

EFEKTIFITAS ENDORPHIN MASSAGE TERHADAP FUNGSI SEKSUAL PEREMPUAN PADA MASA MENOPAUSE

Directory of Open Access Journals (Sweden)

Sri Wahyuni

2017-07-01

Full Text Available Abstract: The purpose of this study is to identify the effectiveness ofendorphine massage on female sexual function during menopause inNgampel District of Kendal Regency. Sampling was done by samplingcriteria acsidental aged less than 60 years old, have a husband, in a healthycondition. Data processing was performed using the Wilcoxon test todetermine differences in sexual function before and after the interventionwhile endorphine effectiveness of massage performed by using MannWhitney.Hasil research: Wilcoxon test showed that there are significantdifferences in sexual function before and after being given endorphineMassage with p value 0.00. While Mann Whitney test showed p value of0.13 and the value of z score of -2.828, which means there is a stronginfluence among endorphine Massage to increased sexual function soendorphine Massage is effective for improving sexual function.Keyword: menopause, endorphin massage, sexual function

The Equivalence between -Stabilities of The Krasnoselskij and The Mann Iterations

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Şoltuz Ştefan M

2007-01-01

Full Text Available We prove the equivalence between the -stabilities of the Krasnoselskij and the Mann iterations; a consequence is the equivalence with the -stability of the Picard-Banach iteration.

Confessions of a serial entrepreneur: a conversation with Alfred E. Mann. Interview by Molly Joel Coye.

Science.gov (United States)

Mann, Alfred E

2006-01-01

In this wide-ranging interview, Alfred Mann describes the activities of several medical technology enterprises with which he is engaged. Several of them are companies that he formed; one is a nonprofit foundation, the Alfred E. Mann Foundation for Biomedical Engineering, founded to establish research-oriented institutes on a dozen university campuses and support their work in developing marketable innovations. Mann discusses the need to consider the cost implications of technology, in the context of U.S. health system reform, and describes several important innovations that have emerged from his companies over the years.

Establishing a Water Resources Resilience Baseline for Mexico City

Science.gov (United States)

Behzadi, F.; Ray, P. A.

2017-12-01

There is a growing concern for the vulnerability of the Mexico City water system to shocks, and the capacity of the system to accommodate climate and demographic change. This study presents a coarse-resolution, lumped model of the water system of Mexico City as a whole, designed to identify system-wide imbalances, and opportunities for large-scale improvements in city-wide resilience through investments in water imports, exports, and storage. In order to investigate the impact of climate change in Mexico City, the annual and monthly trends of precipitation and temperature at 46 stations near or inside the Mexico City were analyzed. The statistical significance of the trends in rainfall and temperature, both over the entire period of record, and the more recent "climate-change-impacted period" (1970-2015), were determined using the non-parametric Mann-Kendall test. Results show a statistically significant increasing trend in the annual mean precipitation, mean temperature, and annual maximum daily temperature. However, minimum daily temperature does not appear to be increasing, and might be decreasing. Water management in Mexico City faces particular challenges, where the winter dry season is warming more quickly than the wet summer season. A stress test of Mexico City water system is conducted to identify vulnerabilities to changes in exogenous factors (esp., climate, demographics, land use). Following on the stress test, the relative merits of adaptation options that might improve the system's resilience and sustainability will be assessed.

Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

Science.gov (United States)

Storlie, Curtis B; Bondell, Howard D; Reich, Brian J; Zhang, Hao Helen

2011-04-01

Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.

Recent Advances and Trends in Nonparametric Statistics

CERN Document Server

Akritas, MG

2003-01-01

The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection o

An Interview with Joe McMann: Lessons Learned from Fifty Years of Observing Hardware and Human Behavior

Science.gov (United States)

McMann, Joe

2011-01-01

Pica Kahn conducted "An Interview with Joe McMann: Lessons Learned in Human and Hardware Behavior" on August 16, 2011. With more than 40 years of experience in the aerospace industry, McMann has gained a wealth of knowledge. This presentation focused on lessons learned in human and hardware behavior. During his many years in the industry, McMann observed that the hardware development process was intertwined with human influences, which impacted the outcome of the product.

Modeling the distribution of extreme share return in Malaysia using Generalized Extreme Value (GEV) distribution

Science.gov (United States)

Hasan, Husna; Radi, Noor Fadhilah Ahmad; Kassim, Suraiya

2012-05-01

Extreme share return in Malaysia is studied. The monthly, quarterly, half yearly and yearly maximum returns are fitted to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are performed to test for stationarity, while Mann-Kendall (MK) test is for the presence of monotonic trend. Maximum Likelihood Estimation (MLE) is used to estimate the parameter while L-moments estimate (LMOM) is used to initialize the MLE optimization routine for the stationary model. Likelihood ratio test is performed to determine the best model. Sherman's goodness of fit test is used to assess the quality of convergence of the GEV distribution by these monthly, quarterly, half yearly and yearly maximum. Returns levels are then estimated for prediction and planning purposes. The results show all maximum returns for all selection periods are stationary. The Mann-Kendall test indicates the existence of trend. Thus, we ought to model for non-stationary model too. Model 2, where the location parameter is increasing with time is the best for all selection intervals. Sherman's goodness of fit test shows that monthly, quarterly, half yearly and yearly maximum converge to the GEV distribution. From the results, it seems reasonable to conclude that yearly maximum is better for the convergence to the GEV distribution especially if longer records are available. Return level estimates, which is the return level (in this study return amount) that is expected to be exceeded, an average, once every t time periods starts to appear in the confidence interval of T = 50 for quarterly, half yearly and yearly maximum.

Kajian Perencanaan Tata Ruang untuk Memfasilitasi Kegiatan Non-Pertanian di Kecamatan Sukorejo, Kabupaten Kendal

OpenAIRE

Ratika Tulus Wahyuhana; Agung Sugiri

2014-01-01

Rural non-farm sector is potential to alleviate poverty and improve rural people’s welfare; however, its development is less encouraged by the government policy, especially the regional spatial plans in Indonesia (Sugiri, et al. 2011). The situation also occurs in Sukorejo District (Kecamatan) of Kendal Regency (Kabupaten) as a potential region for developing rural non-farm sector. This study is aimed at answering the research question of: "How can spatial planning facilitate better the devel...

Temporal variations of reference evapotranspiration and its sensitivity to meteorological factors in Heihe River Basin, China

OpenAIRE

Zhao, Jie; Xu, Zong-xue; Zuo, De-peng; Wang, Xu-ming

2015-01-01

On the basis of daily meteorological data from 15 meteorological stations in the Heihe River Basin (HRB) during the period from 1959 to 2012, long-term trends of reference evapotranspiration (ET0) and key meteorological factors that affect ET0 were analyzed using the Mann-Kendall test. The evaporation paradox was also investigated at 15 meteorological stations. In order to explore the contribution of key meteorological factors to the temporal variation of ET0, a sensitivity coefficient method...

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Science.gov (United States)

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

A Non-Parametric Surrogate-based Test of Significance for T-Wave Alternans Detection

Science.gov (United States)

Nemati, Shamim; Abdala, Omar; Bazán, Violeta; Yim-Yeh, Susie; Malhotra, Atul; Clifford, Gari

2010-01-01

We present a non-parametric adaptive surrogate test that allows for the differentiation of statistically significant T-Wave Alternans (TWA) from alternating patterns that can be solely explained by the statistics of noise. The proposed test is based on estimating the distribution of noise induced alternating patterns in a beat sequence from a set of surrogate data derived from repeated reshuffling of the original beat sequence. Thus, in assessing the significance of the observed alternating patterns in the data no assumptions are made about the underlying noise distribution. In addition, since the distribution of noise-induced alternans magnitudes is calculated separately for each sequence of beats within the analysis window, the method is robust to data non-stationarities in both noise and TWA. The proposed surrogate method for rejecting noise was compared to the standard noise rejection methods used with the Spectral Method (SM) and the Modified Moving Average (MMA) techniques. Using a previously described realistic multi-lead model of TWA, and real physiological noise, we demonstrate the proposed approach reduces false TWA detections, while maintaining a lower missed TWA detection compared with all the other methods tested. A simple averaging-based TWA estimation algorithm was coupled with the surrogate significance testing and was evaluated on three public databases; the Normal Sinus Rhythm Database (NRSDB), the Chronic Heart Failure Database (CHFDB) and the Sudden Cardiac Death Database (SCDDB). Differences in TWA amplitudes between each database were evaluated at matched heart rate (HR) intervals from 40 to 120 beats per minute (BPM). Using the two-sample Kolmogorov-Smirnov test, we found that significant differences in TWA levels exist between each patient group at all decades of heart rates. The most marked difference was generally found at higher heart rates, and the new technique resulted in a larger margin of separability between patient populations than

A ¤nonparametric dynamic additive regression model for longitudinal data

DEFF Research Database (Denmark)

Martinussen, T.; Scheike, T. H.

2000-01-01

dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models......dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models...

PHMB: Utilización del apósito de espuma antimicrobiana (AMD KendallTM (PHMB 0,5% en el tratamiento de las heridas crónicas PHMB: The role ok KendallTM AMD Antimicrobial Foam Dressing (0.5% PHMB in the treatment of wounds

Directory of Open Access Journals (Sweden)

John Timmons

2010-03-01

Full Text Available Abordamos la parte más problemática del tratamiento de las heridas crónicas o agudas, de acuerdo con los profesionales especializados es la infección de la herida. La sobrecarga bacteriana puede retardar la curación de la herida y disminuir la calidad del paciente como consecuencia del aumento del dolor, del exudado y del posible mal olor. Se han recopilado casos clínicos durante los últimos 6 meses en una unidad especializada en el cuidado de heridas de los hospitales Doncaster y Bassetlaw, RU. Estos casos ilustran la variedad de tipos de herida que pueden tratarse con éxito con el nuevo apósito de Espuma antimicrobiano KendallTM AMD (PHMB 0,5%. Se pudo concluir que el apósito de Espuma KendallTM AMD actúa bien como antimicrobiano y como producto de vendaje moderno. Su utilización disminuye la carga bacteriana al tiempo que consigue la absorción del exudado y el mantenimiento de un ambiente óptimo para la curación de la herida.The most troublesome part of wound healing according to the care practitioners is the Wound infection. The presence of excess bacteria in the wound can lead to delayed healing that lead to a reduced quality of life for the patient due to increased pain, higher exudates levels and potential malodor. The following patient case report have been collated over the past six months in a specialist wound care clinic in Doncaster and Bassetlaw, UK. These cases illustrate the range of wound types that have been successfully treated with the new KendallTM AMD Antimicrobial Foam dressing (PHMB 0,5%. The conclusion was that KendallTM AMD Foam dressing functions well as an antimicrobial and a modern wound dressing product. This resulted in consistent lowering of the wound bioburden, absorption of exudates and maintenance of an optimal wound healing environment.

Seasonal trend analysis and ARIMA modeling of relative humidity and wind speed time series around Yamula Dam

Science.gov (United States)

Eymen, Abdurrahman; Köylü, Ümran

2018-02-01

Local climate change is determined by analysis of long-term recorded meteorological data. In the statistical analysis of the meteorological data, the Mann-Kendall rank test, which is one of the non-parametrical tests, has been used; on the other hand, for determining the power of the trend, Theil-Sen method has been used on the data obtained from 16 meteorological stations. The stations cover the provinces of Kayseri, Sivas, Yozgat, and Nevşehir in the Central Anatolia region of Turkey. Changes in land-use affect local climate. Dams are structures that cause major changes on the land. Yamula Dam is located 25 km northwest of Kayseri. The dam has huge water body which is approximately 85 km2. The mentioned tests have been used for detecting the presence of any positive or negative trend in meteorological data. The meteorological data in relation to the seasonal average, maximum, and minimum values of the relative humidity and seasonal average wind speed have been organized as time series and the tests have been conducted accordingly. As a result of these tests, the following have been identified: increase was observed in minimum relative humidity values in the spring, summer, and autumn seasons. As for the seasonal average wind speed, decrease was detected for nine stations in all seasons, whereas increase was observed in four stations. After the trend analysis, pre-dam mean relative humidity time series were modeled with Autoregressive Integrated Moving Averages (ARIMA) model which is statistical modeling tool. Post-dam relative humidity values were predicted by ARIMA models.

The existence of High Conservation Value Forest (HCVF in Perum Perhutani KPH Kendal to support Implementation of FSC Certification

Directory of Open Access Journals (Sweden)

Sulistyowati Sri

2018-01-01

Full Text Available High Conservation Value Forest (HCVF is the identification of High Conservation Values that are important and need to be protected. Under FSC certification mechanism, HCVF becomes one of Principles and Criteria to attain certification. In this study, we identify the existence of HCVF in Perum Perhutani KPH Kendal to support implementation process of FSC certification. Qualitative method was conducted through observation and secondary data from Perum Perhutani KPH Kendal. Data analysis showed through ecolabel certification, Perum Perhutani KPH Kendal has been identified HCVF area covering 2,715.5 hectares consists of HCV 1 until 6. Secondary Natural Forest (HAS Subah and Kaliwungu for Ulolanang and Pagerwunung Nature Reserve buffer zone include as HCV 1.1, conservation area of leopard (Panthera pardus melas and Pangolin (Manis javanica.for HCV 1.2, conservation area of lutung (Trachypiyhecus auratus as endemic species for CITES App I and Critically Endangered species include as HCV 1.3, Goa kiskendo for bats species habitat include as HCV 1.4, regions of interest species for Deer (Cervus timorensis and Kepodang (Oriolus chinensis as HCV 2.3, Germplasm Protection Region/ KPPN area with high biodiversity include as HCV 3, river border area and water springs for HCV 4. While, utilization of firewood, grass for cattle fodder include as HCV 5 and 14 cultural sites include as HCV 6. From monitoring and evaluation of HCVF data, showed that in 2011-2015 the level of diversity for flora and fauna were increased.

The existence of High Conservation Value Forest (HCVF) in Perum Perhutani KPH Kendal to support Implementation of FSC Certification

Science.gov (United States)

Sulistyowati, Sri; Hadi, Sudharto P.

2018-02-01

High Conservation Value Forest (HCVF) is the identification of High Conservation Values that are important and need to be protected. Under FSC certification mechanism, HCVF becomes one of Principles and Criteria to attain certification. In this study, we identify the existence of HCVF in Perum Perhutani KPH Kendal to support implementation process of FSC certification. Qualitative method was conducted through observation and secondary data from Perum Perhutani KPH Kendal. Data analysis showed through ecolabel certification, Perum Perhutani KPH Kendal has been identified HCVF area covering 2,715.5 hectares consists of HCV 1 until 6. Secondary Natural Forest (HAS) Subah and Kaliwungu for Ulolanang and Pagerwunung Nature Reserve buffer zone include as HCV 1.1, conservation area of leopard (Panthera pardus melas) and Pangolin (Manis javanica).for HCV 1.2, conservation area of lutung (Trachypiyhecus auratus) as endemic species for CITES App I and Critically Endangered species include as HCV 1.3, Goa kiskendo for bats species habitat include as HCV 1.4, regions of interest species for Deer (Cervus timorensis) and Kepodang (Oriolus chinensis) as HCV 2.3, Germplasm Protection Region/ KPPN area with high biodiversity include as HCV 3, river border area and water springs for HCV 4. While, utilization of firewood, grass for cattle fodder include as HCV 5 and 14 cultural sites include as HCV 6. From monitoring and evaluation of HCVF data, showed that in 2011-2015 the level of diversity for flora and fauna were increased.

Statistical significance of trends in monthly heavy precipitation over the US

KAUST Repository

Mahajan, Salil

2011-05-11

Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.

Nonparametric analysis of blocked ordered categories data: some examples revisited

Directory of Open Access Journals (Sweden)

O. Thas

2006-08-01

Full Text Available Nonparametric analysis for general block designs can be given by using the Cochran-Mantel-Haenszel (CMH statistics. We demonstrate this with four examples and note that several well-known nonparametric statistics are special cases of CMH statistics.

Nonparametric Mixture Models for Supervised Image Parcellation.

Science.gov (United States)

Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

2009-09-01

We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

Thomas Mann's "Tobias Mindernickel" in Light of Sartre's "Being-for-Others"

Directory of Open Access Journals (Sweden)

Beth Bjorklund

1978-01-01

Full Text Available Sartre's analysis of "Being-for-Others" in Being and Nothingness describes the Self-Other relationship as essentially one of conflict, with the Self attempting either to dominate or to be dominated by the Other. Subject-Object relations are a common theme also in the early works of Thomas Mann, who gives artistic expression to many of the same problems which Sartre later formalized in a philosophical theory. The sado-masochistic character, which is portrayed in several of Thomas Mann's narratives, receives its strongest expression in the story "Tobias Mindernickel," which is here singled out for analysis. Humiliation gives rise to aggression, as the protagonist feels both an attraction and a repulsion for his surrogate lover, a dog. The interpersonal relationships revealed here serve as paradigmatic illustration of Sartre's theory of "Concrete Relations with Others."

Changes and trends of seasonal total rainfall in the province of Istanbul, Turkey

Directory of Open Access Journals (Sweden)

İbrahim Yurtseven

2017-01-01

Full Text Available Changes and trends of seasonal total rainfall in the province of Istanbul, Turkey Abstract: Several studies revealed that climate change can affect local and regional precipitation patterns. Long term trends and cycles in precipitation is important for the health of ecosystems in the region. The possible impacts in near future can affect the forest and water resources of Istanbul. In this study, daily, monthly, seasonal and annual precipitation analyses for the different meteorology stations were examined for the İstanbul province. Northern and southern different climatic conditions of İstanbul have been effective selection of the station. The Mann-Kendall test results showed that there is positive statistically significant trend in some meteorology stations. According to Mann-Kendall results the increased fall precipitation trend were found in Florya, Kireçburnu ve Kumköy meteorology stations and decreased summer precipitation trend were found in Göztepe meteorology stations Keywords: Mann-Kendall trend analysis, precipitation time series, the regional precipitation reactions analysis, climate change İstanbul ilinde mevsimsel toplam yağışların değişimleri ve eğilimleri Özet: İklim değişikliğinin bölgesel ve yöresel ölçekte yağış rejimi üzerinde etkileri olabileceği birçok araştırma ile ortaya konulmuştur. Yağış serilerindeki uzun dönemli yönelimler ve döngüler yöredeki ekosistemlerin sağlığı ve geleceği açısından büyük önem arzetmektedir. İstanbul ilinde önümüzdeki dönemde gerçekleşebilecek etkiler ise hem su kaynakları hem de ormanlar üzerinde önemli sonuçlar ortaya çıkarabilir. Bu çalışmada İstanbul iline ait farklı meteoroloji istasyonlarının uzun dönemli mevsimlik verileri araştırılmıştır. Çalışmadaki amacımız ileriye dönük tahminlerdeki belirsizlikleri belli oranda ortadan kaldırabilecek geçmişe dönük veriler yardımıyla istatistiksel analizleri ger

Temporal and Spatial Pattern of Changes of Extreme Precipitation in the Middle and Lower Yangtze River Basin (YRB) during 1960 to 2012

Science.gov (United States)

Wu, Y.; Wu, S.; Wen, J.; Xu, M.; Tan, J.

2013-12-01

The Yangtze River is the longest river in China, with its river basin covering an area of 1.8 million sq km, encompassing about one fifth of China's total territory, one third of the nation's total population, and one quarter of its total arable land. Flooding resulted from extreme precipitation has always been a major problem for the middle and lower part of the YRB, particularly during the monsoon season of eastern China from May to August. Meanwhile, the relatively dense population and large cities in this region make the floods more deadly and costly. In this study we aim to establish the temporal and spatial patterns of changes in extreme precipitation in the middle and lower YRB using daily precipitation data from 71 stations in the area from 1960 to 2012. It is hoped that this study will provide useful information for better flood control. In this study, we defined and examined three major indices. Extreme precipitation frequency is defined as number of days per year with precipitation exceeding the 95th percentile for the base period of 1961 - 1990. Extreme precipitation amount is defined as the total amount of precipitation from these days. Extreme precipitation intensity is defined as the amount divided by frequency. We used non-parametric Thiel-Sen method to estimate the rate of change at each station, and Mann-Kendall test for the significance of the trend. Using Thiessen polygons, we also calculated the area-weighted mean of station trends to get the total trend for the entire study area. Abrupt changes in the time series was detected by using Mann-Kendall test and the Moving-t test methods. Our results show that there is an increasing trend of for the frequency, amount, and intensity of extreme precipitation in the study region. Of the three indicators, the extreme precipitation amount increased most, and its abrupt change point happened in1987. Between the period before and after 1987, the mean annual amount, intensity and frequency of extreme

MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

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Kuczmarski Thomas A

2006-10-01

Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein

FAKTOR-FAKTOR YANG MEMPENGARUHI KESULITAN BELAJAR PADA MATA PELAJARAN OTOMATISASI PERKANTORAN KELAS X PROGRAM STUDI ADMINISTRASI PERKANTORAN DI SMK NEGERI 1 KENDAL

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Moh Lutfi Fadil

2015-06-01

Full Text Available Kesulitan belajar siswa perlu diketahui penyebabnya, agar dapat membantu memaksimalkan belajar siswa. Penelitian ini bertujuan untuk (1 mengetahui faktor-faktor apa saja yang mempengaruhi kesulitan belajar siswa kelas X program studi administrasi perkantoran di SMK Negeri 1 Kendal.(2 berapa besar kontribusi pengaruh yang diberikan oleh faktor-faktor yang mempengaruhi kesulitan belajar siswa kelas X program studi administrasi perkantoran di SMK Negeri 1 Kendal.Teknik pengumpulan data menggunakan angket, dokumentasi dan wawancara. Teknik analisis data menggunakan analisis faktor dan deskriptif persentase.Hasil analisis faktor menunjukan bahwa dari 17 variabel direduksi menjadi 16 variabel yang mengelompok menjadi 6 faktor baru yang mempengaruhi kesulitan belajar siswa antara lain yaitu (1 Faktor Pembelajaran sebesar 26,958%, (2 Faktor keadaan sekolah dan keluarga sebesar 12,168%, (3 Faktor kondisi jasmani dan rohani sebesar 10,048%, (4 Faktor lingkungan masyarakat sebesar 7,069%, (5 Faktor pergaulan sebesar 6,578% dan (6 Faktor kecerdasan sebesar 6,276%. Learning difficulties students need to know the cause, in order to help maximize student learning. This study aims to (1 determine the factors that influence the difficulty of class X student office administration courses at SMK Negeri 1 Kendal. (2 how much contribution the influence exerted by factors that affect students' learning difficulties in class X office administration courses at SMK Negeri 1 Kendal. The technique of collecting data using questionnaires, documentation and interviews. Data were analyzed using factor analysis and descriptive percentages. Results of factor analysis showed that of the 17 variables reduced to 16 variables grouped into 6 new factor affecting students' learning difficulties, among others: (1 Learning factor of 26.958%, (2 factors of school and family circumstances amounting to 12.168%, (3 physical and spiritual condition factor of 10.048%, (4 environmental

Nonparametric Monitoring for Geotechnical Structures Subject to Long-Term Environmental Change

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Hae-Bum Yun

2011-01-01

Full Text Available A nonparametric, data-driven methodology of monitoring for geotechnical structures subject to long-term environmental change is discussed. Avoiding physical assumptions or excessive simplification of the monitored structures, the nonparametric monitoring methodology presented in this paper provides reliable performance-related information particularly when the collection of sensor data is limited. For the validation of the nonparametric methodology, a field case study was performed using a full-scale retaining wall, which had been monitored for three years using three tilt gauges. Using the very limited sensor data, it is demonstrated that important performance-related information, such as drainage performance and sensor damage, could be disentangled from significant daily, seasonal and multiyear environmental variations. Extensive literature review on recent developments of parametric and nonparametric data processing techniques for geotechnical applications is also presented.

Nonparametric Estimation of Distributions in Random Effects Models

KAUST Repository

Hart, Jeffrey D.

2011-01-01

We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.

MODEL PENGEMBANGAN LOMPAT WARNA DALAM PEMBELAJARAN PENJASORKES UNTUK MENINGKATKAN MOTIVASI GERAK SISWA TUNARUNGU WICARA DI SDLB ABC ”SWADAYA” KENDAL

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Rian Chandra Rahadika Sunu

2015-04-01

Full Text Available The purpose of this study is to produce a model of learning development that aims to increase motivation for students with hearing and speech impaired movement in SDLB ABC "Organization" Kendal. This study uses action research. The method of research is the development of models of learning: 1 a preliminary investigation and information gathering, field observations and literature review, 2 develop early prodak form, 3 evaluation of experts, 4 revision of the first product, 5 field test, 6 revision of the final product, 7 final jump game model of color. The trial results obtained evaluation data also includes cognitive, effective and psychomotor ie, from experts penjas 83% (good, a 87% Learning (good, a small test group 95.83% (excellent, and a field test 95% (very good. Based on the available data it can be concluded that the learning model of this color can be used to jump to the deaf and speech impaired students SDLB

portfolio optimization based on nonparametric estimation methods

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mahsa ghandehari

2017-03-01

Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.

Robustifying Bayesian nonparametric mixtures for count data.

Science.gov (United States)

Canale, Antonio; Prünster, Igor

2017-03-01

Our motivating application stems from surveys of natural populations and is characterized by large spatial heterogeneity in the counts, which makes parametric approaches to modeling local animal abundance too restrictive. We adopt a Bayesian nonparametric approach based on mixture models and innovate with respect to popular Dirichlet process mixture of Poisson kernels by increasing the model flexibility at the level both of the kernel and the nonparametric mixing measure. This allows to derive accurate and robust estimates of the distribution of local animal abundance and of the corresponding clusters. The application and a simulation study for different scenarios yield also some general methodological implications. Adding flexibility solely at the level of the mixing measure does not improve inferences, since its impact is severely limited by the rigidity of the Poisson kernel with considerable consequences in terms of bias. However, once a kernel more flexible than the Poisson is chosen, inferences can be robustified by choosing a prior more general than the Dirichlet process. Therefore, to improve the performance of Bayesian nonparametric mixtures for count data one has to enrich the model simultaneously at both levels, the kernel and the mixing measure. © 2016, The International Biometric Society.

On the error estimation and T-stability of the Mann iteration

NARCIS (Netherlands)

Maruster, Laura; Maruster, St.

2015-01-01

A formula of error estimation of Mann iteration is given in the case of strongly demicontractive mappings. Based on this estimation, a condition of strong convergence is obtained for the same class of mappings. T-stability for a particular case of strongly demicontractive mappings is proved. Some

Concordance-based Kendall's Correlation for Computationally-Light vs. Computationally-Heavy Centrality Metrics: Lower Bound for Correlation

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Natarajan Meghanathan

2017-01-01

Full Text Available We identify three different levels of correlation (pair-wise relative ordering, network-wide ranking and linear regression that could be assessed between a computationally-light centrality metric and a computationally-heavy centrality metric for real-world networks. The Kendall's concordance-based correlation measure could be used to quantitatively assess how well we could consider the relative ordering of two vertices vi and vj with respect to a computationally-light centrality metric as the relative ordering of the same two vertices with respect to a computationally-heavy centrality metric. We hypothesize that the pair-wise relative ordering (concordance-based assessment of the correlation between centrality metrics is the most strictest of all the three levels of correlation and claim that the Kendall's concordance-based correlation coefficient will be lower than the correlation coefficient observed with the more relaxed levels of correlation measures (linear regression-based Pearson's product-moment correlation coefficient and the network wide ranking-based Spearman's correlation coefficient. We validate our hypothesis by evaluating the three correlation coefficients between two sets of centrality metrics: the computationally-light degree and local clustering coefficient complement-based degree centrality metrics and the computationally-heavy eigenvector centrality, betweenness centrality and closeness centrality metrics for a diverse collection of 50 real-world networks.

Parametric and Non-Parametric System Modelling

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg

1999-01-01

the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...

Partielle endokrine Veränderungen des alternden Mannes (PEVAM: Facts and Fiction

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Ponholzer A

2000-01-01

Full Text Available Die kontinuierliche Abnahme der Sexualhormone Testosteron und Dehydroepiandrosteronsulfat (DHEA-S in Verbindung mit dem Altern des Mannes steht heutzutage außer Zweifel [1, 2]. Die beim Mann zu beobachtenden Änderungen im Hormonhaushalt unterscheiden sich von denen der Frau durch den langsamen, stetigen Verlauf und die oftmalige Erhaltung der Fertilität bis ins höchste Alter. Es ist daher falsch, von einem "Klimakterium virile" oder von "Andropause" zu sprechen. Das Ausmaß der Abnahme der Androgenspiegel unterliegt, ebenso wie das Bestehen einer assoziierten Symptomatik, einer hohen interindividuellen Streuung. Unter dem Begriff PADAM (partielles Androgendefizit des alternden Mannes werden als Auswirkung verminderter Androgenspiegel vielfältige Symptome beschrieben, wie zum Beispiel Hitzewallungen, Schlafstörungen, Einschränkungen des Wohlbefindens und der Sexualität sowie Abnahme von Knochendichte und Muskelmasse oder Veränderung von Fettverteilungsmuster und Gesamtkörperfettanteil. Bei Vorliegen von einem oder mehreren der oben genannten Symptome in Verbindung mit entsprechend verminderten Testosteronspiegeln existiert die Möglichkeit einer Substitutionstherapie, sowohl zur Prävention, als auch zur Therapie negativer Auswirkungen des Mangels. Potentielle Risiken einer Androgentherapie scheinen kontrollierbar, werden aber erst in Zukunft durch umfassende Langzeitstudien in ihrem ganzen Ausmaß beurteilbar sein. Andere Hormonsysteme, wie etwa Wachstumshormone (GH oder Melatonin unterliegen ebenfalls einer altersassozierten Abnahme. Auch hier darf eine Auswirkung auf die Lebensqualität angenommen werden, die Sinnhaftigkeit einer Ersatztherapie ist bei GH und Melatonin, wie auch bei DHEA-S, jedoch umstritten.

Accelerating medical innovation at USC: realizing the dream of Alfred E. Mann.

Science.gov (United States)

Gosset, Nathalie; Lasch, Jonathan G

2012-07-01

Alfred E. Mann's vision is to create organizations that will help medical innovations born in academic environments evolve into commercially fit solutions, without the risk of being abandoned under the financial pressures early stage start-ups often experience. In 1998, Mann worked with Stephen Sample, president of USC, to create the first AMI for Biomedical Engineering, an organization fueled by an endowment valued at approximately US$160 million today. Technology-acceleration centers come in different flavors. AMI USC's recipe has evolved since its creation, with edits that incorporate lessons learned and improvements brought by its expanding network of talented resource people. Its 15-member staff, consisting of three-fourths industry professionals, includes seasoned generalists and specialists in medical technology commercialization. Although the support varies with each invention, some recurring ingredients weave into the AMI approach to accelerating medical innovation.

VIPER: Chronic Pain after Amputation: Inflammatory Mechanisms, Novel Analgesic Pathways, and Improved Patient Safety

Science.gov (United States)

2016-10-01

Whitney U test for evaluating differences in inflammatory mediators between groups (Case vs. Control) and used nonparametric correlations (Spearman’s rho...responses to acute pain. PAIN 2008;140:135–144. [10] Gordon S, Martinez FO. Alternative activation of macrophages: mechanism and functions...Concentrations in Cases vs. Controls. Mediator Case (n=36) Median (Range) Control (n=40) Median (Range) Mann- Whitney U Test (p value) IFN

Network structure exploration via Bayesian nonparametric models

International Nuclear Information System (INIS)

Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

2015-01-01

Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.

Science.gov (United States)

Teixeira, Ana P; Clemente, João J; Cunha, António E; Carrondo, Manuel J T; Oliveira, Rui

2006-01-01

This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.

Nonparametric methods for volatility density estimation

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2009-01-01

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

Quantal Response: Nonparametric Modeling

Science.gov (United States)

2017-01-01

capture the behavior of observed phenomena. Higher-order polynomial and finite-dimensional spline basis models allow for more complicated responses as the...flexibility as these are nonparametric (not constrained to any particular functional form). These should be useful in identifying nonstandard behavior via... deviance ∆ = −2 log(Lreduced/Lfull) is defined in terms of the likelihood function L. For normal error, Lfull = 1, and based on Eq. A-2, we have log

Statistical Analysis of Long-Term Trend of Performance, Production and Cultivated Area of 17 Field Crops Khorasan Razavi Province

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H. Zareabyaneh

2014-12-01

Full Text Available Any planning for the future requires estimates of future conditions. It is possible to study changes over time series. In this study, changes of production and cultivated area of 17 field crops of Khorasan Razavi province in a 25-year period were determined with Mann - Kendall test, Sen’s Estimator Slope and linear regression. Analysis of the three tests showed that performance of 76.5% from yield, 88.2% from area under cultivation and 55.8% from agricultural production were significant at the 0.01 and 0.05 level. On the other hand, trend of yields 58.8% was increase, 17.7% was reduced and 23.5% was no significant trend. Similarly, trend of 23.5% from area under cultivation was acreage, 64.7% was reduction, and 11.8% was no significant trend. For production variable, 29.4% was significantly increased and 29.4% was significant reduction. More detailed analysis showed that performance, production and area under cultivation of three crops of cotton, grain and tomatoes increased significantly. Results of all three methods showed the highest trend of negatively performance and area under cultivation variation is related to pea and melon respectively. Furthermore, most of the positive trend in production of tomatoes and grain, performance in onions, potatoes and tomatoes and area under cultivation in tomato observed. The results showed that linear trend and the nonparametric tests of important products of province: wheat, barley, sugar beet, cotton, melons, watermelons and tomatoes in 0.01 were significant. This result shows the importance of these yields in gross state province product.

Changes in late-winter snowpack depth, water equivalent, and density in Maine, 1926-2004

Science.gov (United States)

Hodgkins, Glenn A.; Dudley, Robert W.

2006-03-01

Twenty-three snow-course sites in and near Maine, USA, with records spanning at least 50 years through to 2004 were tested for changes over time in snowpack depth, water equivalent, and density in March and April. Of the 23 sites, 18 had a significant decrease (Mann-Kendall test, p 1950s and 1960s, and densities peaked in the most recent decade. Previous studies in western North America also found a water-equivalent peak in the third quarter of the 20th century. Published in 2006 by John Wiley & Sons, Ltd.Received: 14 June 2005; Accepted: 7 October 2005

Speaker Linking and Applications using Non-Parametric Hashing Methods

Science.gov (United States)

2016-09-08

nonparametric estimate of a multivariate density function,” The Annals of Math- ematical Statistics , vol. 36, no. 3, pp. 1049–1051, 1965. [9] E. A. Patrick...Speaker Linking and Applications using Non-Parametric Hashing Methods† Douglas Sturim and William M. Campbell MIT Lincoln Laboratory, Lexington, MA...with many approaches [1, 2]. For this paper, we focus on using i-vectors [2], but the methods apply to any embedding. For the task of speaker QBE and

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

Science.gov (United States)

Park, Saerom; Lee, Jaewook; Son, Youngdoo

2016-01-01

Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

Science.gov (United States)

Zhang, Qingyang

2018-05-16

Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

Efeito da fortificação alimentar com ácido fólico na prevalência de defeitos do tubo neural Efecto de la fortificación alimentaria con ácido fólico en la prevalencia de defectos del tubo neural Effects of folic acid fortification on the prevalence of neural tube defects

Directory of Open Access Journals (Sweden)

Sâmya Silva Pacheco

2009-08-01

Full Text Available OBJETIVO:Analisar o efeito de alimentos fortificados com ácido fólico na prevalência de defeitos de fechamento do tubo neural entre nascidos vivos. MÉTODOS: Estudo longitudinal de nascidos vivos do município de Recife (PE entre 2000 e 2006. Os dados pesquisados foram obtidos do Sistema Nacional de Informações de Nascidos Vivos. Os defeitos de fechamento do tubo neural foram definidos de acordo com o Código Internacional de Doenças-10ª Revisão: anencefalia, encefalocele e espinha bífida. Compararam-se as prevalências nos períodos anterior (2000-2004 e posterior (2005-2006 ao período mandatório à fortificação. Analisou-se a tendência temporal das prevalências trimestrais de defeitos do fechamento do tubo neural pelos testes de Mann-Kendall e Sen's Slope. RESULTADOS: Não se identificou tendência de redução na ocorrência do desfecho (Teste de Mann-Kendall; p= 0,270; Sen's Slope =-0,008 no período estudado. Não houve diferença estatisticamente significativa entre as prevalências de defeitos do fechamento do tubo neural nos períodos anterior e posterior à fortificação dos alimentos com acido fólico de acordo com as características maternas. CONCLUSÕES: Embora não tenha sido observada redução dos defeitos do fechamento do tubo neural após o período mandatório de fortificação de alimentos com ácido fólico, os resultados encontrados não permitem descartar o seu benefício na prevenção desta malformação. São necessários estudos avaliando maior período e considerando o nível de consumo dos produtos fortificados pelas mulheres em idade fértil.OBJETIVO:Analizar el efecto de alimentos fortificados con ácido fólico en la prevalencia de defectos del cierre del tubo neural entre nacidos vivos. MÉTODOS: Estudio longitudinal de nacidos vivos del municipio de Recife (Noreste de Brasil, entre 2000 y 2006. Los datos pesquisados fueron obtenidos del Sistema Nacional de Informaciones de Nacidos Vivos. Los

Non-Parametric Estimation of Correlation Functions

DEFF Research Database (Denmark)

Brincker, Rune; Rytter, Anders; Krenk, Steen

In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...

Application of nonparametric statistic method for DNBR limit calculation

International Nuclear Information System (INIS)

Dong Bo; Kuang Bo; Zhu Xuenong

2013-01-01

Background: Nonparametric statistical method is a kind of statistical inference method not depending on a certain distribution; it calculates the tolerance limits under certain probability level and confidence through sampling methods. The DNBR margin is one important parameter of NPP design, which presents the safety level of NPP. Purpose and Methods: This paper uses nonparametric statistical method basing on Wilks formula and VIPER-01 subchannel analysis code to calculate the DNBR design limits (DL) of 300 MW NPP (Nuclear Power Plant) during the complete loss of flow accident, simultaneously compared with the DL of DNBR through means of ITDP to get certain DNBR margin. Results: The results indicate that this method can gain 2.96% DNBR margin more than that obtained by ITDP methodology. Conclusions: Because of the reduction of the conservation during analysis process, the nonparametric statistical method can provide greater DNBR margin and the increase of DNBR margin is benefited for the upgrading of core refuel scheme. (authors)

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

Directory of Open Access Journals (Sweden)

Saerom Park

Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

Evaluation of recent hydro-climatic changes in four tributaries of the Niger River Basin (West Africa)

CSIR Research Space (South Africa)

Badou, DF

2017-10-01

Full Text Available West Africa experienced severe drought during the 1970s and 1980s, posing a threat to water resources. A wetter climate more recently suggests recovery from the drought. The Mann-Kendall trend and Theil-Sen’s slope estimator were applied to detect...

Multi-sample nonparametric treatments comparison in medical ...

African Journals Online (AJOL)

Multi-sample nonparametric treatments comparison in medical follow-up study with unequal observation processes through simulation and bladder tumour case study. P. L. Tan, N.A. Ibrahim, M.B. Adam, J. Arasan ...

PERAN SELF-REGULATED LEARNING DALAM MEMODERASI PENGGARUH LINGKUNGAN TEMAN SEBAYA DAN MEDIA SOSIAL TERHADAP PRESTASI BELAJAR MATA PELAJARAN AKUNTANSI KOMPUTERSISWA KELAS XI KOMPETENSI KEAHLIAN AKUNTANSI SMK N 1 KENDAL

Directory of Open Access Journals (Sweden)

Elsa Puspasari

2015-11-01

accounting in SMK N 1 Kendal. The population in this study was eleventh grade students in accounting competence skill in academic year 2014/2015. The number of the sample was 84 students. They were proportional random sampling sample. The methods that were used in collecting data were documentation and questionnaire. The analytical methods that were used were descriptive analysis techniques and absolute differencevalue test. The descriptive analysis showed that peer environment, social media, self regulated learning were enough. And the students accounting computer learning achievement was low.

Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

Science.gov (United States)

Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

2013-04-01

In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

Tendências hidrológicas anuais e sazonais na bacia do Rio Paraibuna, Parque Estadual da Serra do Mar (SP)

OpenAIRE

Vilanova,Mateus Ricardo Nogueira

2014-01-01

O presente trabalho avalia a existência de tendências monotônicas em séries anuais e sazonais de vazão e chuva, no trecho da Bacia do Rio Paraibuna localizado entre os Núcleos Cunha e Santa Virgínia, Parque Estadual da Serra do Mar (SP). O teste de Mann-Kendall foi aplicado a séries destas variáveis, em diversos intervalos no período de 1967 a 2011. Tendências negativas estatisticamente significativas foram detectadas nas séries de c...

Development of the Crohn's disease digestive damage score, the Lémann score

DEFF Research Database (Denmark)

Pariente, Benjamin; Cosnes, Jacques; Danese, Silvio

2011-01-01

is to outline the methods to develop an instrument that can measure cumulative bowel damage. The project is being conducted by the International Program to develop New Indexes in Crohn's disease (IPNIC) group. This instrument, called the Crohn's Disease Digestive Damage Score (the Lémann score), should take...

Essays on nonparametric econometrics of stochastic volatility

NARCIS (Netherlands)

Zu, Y.

2012-01-01

Volatility is a concept that describes the variation of financial returns. Measuring and modelling volatility dynamics is an important aspect of financial econometrics. This thesis is concerned with nonparametric approaches to volatility measurement and volatility model validation.

Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types

International Nuclear Information System (INIS)

Aboalkhair, Ahmad M.; Coolen, Frank P.A.; MacPhee, Iain M.

2014-01-01

Nonparametric predictive inference for system reliability has recently been presented, with specific focus on k-out-of-m:G systems. The reliability of systems is quantified by lower and upper probabilities of system functioning, given binary test results on components, taking uncertainty about component functioning and indeterminacy due to limited test information explicitly into account. Thus far, systems considered were series configurations of subsystems, with each subsystem i a k i -out-of-m i :G system which consisted of only one type of components. Key results are briefly summarized in this paper, and as an important generalization new results are presented for a single k-out-of-m:G system consisting of components of multiple types. The important aspects of redundancy and diversity for such systems are discussed. - Highlights: • New results on nonparametric predictive inference for system reliability. • Prediction of system reliability based on test data for components. • New insights on system redundancy optimization and diversity. • Components that appear inferior in tests may be included to enhance redundancy

A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis

International Nuclear Information System (INIS)

Janurová, Kateřina; Briš, Radim

2014-01-01

Medical survival right-censored data of about 850 patients are evaluated to analyze the uncertainty related to the risk of mortality on one hand and compare two basic surgery techniques in the context of risk of mortality on the other hand. Colorectal data come from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either traditional (open) or minimally invasive (laparoscopic). Basic question arising at the colectomy operation is, which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify probability of mortality with uncertainties. In fact, complement of the probability to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan–Meier estimator of survival function in connection with Greenwood's formula and the Nelson–Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been compared to evaluate risk of mortality in the context of mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Both nonparametric approaches led to the same conclusion, that the minimally invasive operating technique guarantees the patient significantly longer survival time in comparison with the traditional operating technique

Price Overreactions in the Cryptocurrency Market

OpenAIRE

Caporale, Guglielmo Maria; Plastun, Alex

2018-01-01

This paper examines price overreactions in the case of the following cryptocurrencies: BitCoin, LiteCoin, Ripple and Dash. A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann-Whitney U test) tests confirm the presence of price patterns after overreactions: the next-day price changes in both directions are bigger than after "normal" days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited...

Nonparametric Statistics Test Software Package.

Science.gov (United States)

1983-09-01

25 I1l,lCELL WRITE (NCF,12 ) IvE (I ,RCCT(I) 122 FORMAT(IlXt 3(H5 9 1) IF( IeLT *NCELL) WRITE (NOF1123 J PARTV(I1J 123 FORMAT( Xll----’,FIo.3J 25 CONT...the user’s entries. Its purpose is to write two types of files needed by the program Crunch: the data file, and the option file. 211 Iuill rateLchiavar...data file and communicate the choice of test and test parameters to Crunch. After a data file is written, Lochinvar prompts the writing of the

“Far finta”, raffigurare, narrare: uno sguardo su Mimesi come far finta di Kendall Lewis Walton

Directory of Open Access Journals (Sweden)

Chiara Bisignano

2015-11-01

Full Text Available Il saggio descrive e analizza la teoria della rappresentazionalità presentata da Kendall Walton in Mimesi come far finta. Le rappresentazioni sono supporti atti a suscitare un far finta che si esplica come un immaginare proposizionale: ecco la tesi dell’autore. I caratteri di tale far finta, la dinamica della partecipazione, la distinzione tra figuralità e verbalità, e il problema delle entità fittizie, sono i punti cardine della proposta waltoniana. La questione dell’esperienza, e la sua possibile, originaria, tematizzazione estetica; il tema del rapporto tra emozioni fittizie e reali; e la maniera specifica in  cui l’autore intende la mimesi della rappresentazione, sono, in particolare, gli aspetti che il saggio problematizza più estesamente.The essay is intended to describe while analyzing the theory of representationality as presented by Kendall Walton in Mimesis as Make-Believe. Representations are mediums leading to provoke a make-believe – its kind building up as propositional acts of imagination: such the thesis that the author asserts. Features of this make-believe, the dynamics of participation, the distinction between figurality and verbality, the problem of fictional entities, those are the nodal joints of the waltonian proposal. The question of experience – and its possible, originary, aesthetical thematization, the thematization of the relation between fictional and real emotions, and the specific sense in which the author draws the mimesis proper to representation: such the aspects which the present essay is mostly concerned with. 

Hydrochemical evaluation of river water quality—a case study: Horroud River

Science.gov (United States)

Falah, Fatemeh; Haghizadeh, Ali

2017-12-01

Surface waters, especially rivers are the most important sources of water supply for drinking and agricultural purposes. Water with desirable quality is necessary for human life. Therefore, knowledge of water quality and its temporal changes is of particular importance in sustainable management of water resources. In this study, available data during 20 years from two hydrometry stations located in the way of Horroud River in Lorestan province were used and analyzed using Aq.QA software. Piper, Schoeller, Stiff, and Wilcox diagram were drawn and Mann-Kendal test was used for determining data trend. According to Wilcox diagram, water of this river in both stations is placed in c2s1 class which is good for agricultural purposes, and according to Schoeller diagram, there is no restrict for drinking purposes. Results of Man-Kendal test show increasing trend for colorine, EC, TDS while decreasing trend for potassium in Kakareza station. On the other hand in Dehnu station, positive trend was seen in calcium and colorine while negative trend for sulfate and potassium. For other variables, no specific trend was found.

Modeling extreme PM10 concentration in Malaysia using generalized extreme value distribution

Science.gov (United States)

Hasan, Husna; Mansor, Nadiah; Salleh, Nur Hanim Mohd

2015-05-01

Extreme PM10 concentration from the Air Pollutant Index (API) at thirteen monitoring stations in Malaysia is modeled using the Generalized Extreme Value (GEV) distribution. The data is blocked into monthly selection period. The Mann-Kendall (MK) test suggests a non-stationary model so two models are considered for the stations with trend. The likelihood ratio test is used to determine the best fitted model and the result shows that only two stations favor the non-stationary model (Model 2) while the other eleven stations favor stationary model (Model 1). The return level of PM10 concentration that is expected to exceed the maximum once within a selected period is obtained.

Nonparametric predictive inference in statistical process control

NARCIS (Netherlands)

Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

2000-01-01

New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on

Considerações estatísticas relativas a seis séries mensais de temperatura do ar da Secretaria de Agricultura e Abastecimento do Estado de São Paulo Statistical considerations of six monthly air temperature series of the State of São Paulo, Brazil

Directory of Open Access Journals (Sweden)

Gabriel Constantino Blain

2011-06-01

Full Text Available O objetivo do trabalho foi detectar tendências e variações climáticas nas séries mensais de temperatura máxima (Tmax e mínima (Tmin do Estado de São Paulo. A fim de obter melhor adequação, entre a probabilidade de ocorrência dos erros estatísticos tipo I e II, foram utilizados métodos paramétricos (teste t, F e razão da verossimilhança e não paramétricos (teste sazonal de Mann-Kendall e de Pettitt. As séries de Tmin das localidades de Campinas, Cordeirópolis, Ribeirão Preto e, especialmente Ubatuba, apresentam fortes indícios de tendências e variações climáticas nos últimos 60 anos. Nas séries de Monte Alegre do Sul e Pindorama tais indícios são observados de forma pouco significativa. As alterações de ordem climática observadas nas séries de Tmax são bastante inferiores às observadas nas séries de Tmin. Dentre todas as localidades analisadas, a de Ubatuba foi a que apresentou as tendências de elevação mais significativas nos dados de temperatura do ar. Os resultados também indicaram que no mês de Abril podem ser verificados, em todas as seis localidades, os indícios mais significativos de elevação nos valores mensais da Tmax e, em especial, da Tmin. Em contra partida, o mês de Setembro mostrou-se o menos sujeito a elevação nos valores dessas duas variáveis meteorológicas.The aim of the work was to detect trends and climate variations in monthly maximum (Tmax and minimum (Tmin air temperature series of the State of São Paulo. In order to obtain a better balance between the probabilities associated with type I and II errors, parametric methods (tests t, F and the likelihood ratio test and non-parametric methods (Seasonal Mann-Kendall test and Pettitt test were used. In the series of Campinas-SP, Cordeirópolis-SP, Ribeirão Preto-SP and, especially Ubatuba-SP, strong evidences of climate trends and climate variations in the last 60 years were detected. In the Monte Alegre do Sul-SP and Pindorama

Nonparametric instrumental regression with non-convex constraints

International Nuclear Information System (INIS)

Grasmair, M; Scherzer, O; Vanhems, A

2013-01-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition. (paper)

Nonparametric instrumental regression with non-convex constraints

Science.gov (United States)

Grasmair, M.; Scherzer, O.; Vanhems, A.

2013-03-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

"German Culture is where I am": Thomas Mann in Exile

OpenAIRE

Helmut Koopmann

1982-01-01

Thomas Mann in exile reacted like many writers expelled from Germany: totally irritated he tried to defend his own identity by claiming that he was still the leading representative of Germany. But about 1938 a process of dissociation from Germany started which led to sharp remarks on Germany in his The Beloved Returns , to his conviction that German culture was where he lived and to the acknowledgement of America as his new home. Traces of his experience of exile, and a late answer on his se...

Exact nonparametric confidence bands for the survivor function.

Science.gov (United States)

Matthews, David

2013-10-12

A method to produce exact simultaneous confidence bands for the empirical cumulative distribution function that was first described by Owen, and subsequently corrected by Jager and Wellner, is the starting point for deriving exact nonparametric confidence bands for the survivor function of any positive random variable. We invert a nonparametric likelihood test of uniformity, constructed from the Kaplan-Meier estimator of the survivor function, to obtain simultaneous lower and upper bands for the function of interest with specified global confidence level. The method involves calculating a null distribution and associated critical value for each observed sample configuration. However, Noe recursions and the Van Wijngaarden-Decker-Brent root-finding algorithm provide the necessary tools for efficient computation of these exact bounds. Various aspects of the effect of right censoring on these exact bands are investigated, using as illustrations two observational studies of survival experience among non-Hodgkin's lymphoma patients and a much larger group of subjects with advanced lung cancer enrolled in trials within the North Central Cancer Treatment Group. Monte Carlo simulations confirm the merits of the proposed method of deriving simultaneous interval estimates of the survivor function across the entire range of the observed sample. This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada. It was begun while the author was visiting the Department of Statistics, University of Auckland, and completed during a subsequent sojourn at the Medical Research Council Biostatistics Unit in Cambridge. The support of both institutions, in addition to that of NSERC and the University of Waterloo, is greatly appreciated.

Nonparametric conditional predictive regions for time series

NARCIS (Netherlands)

de Gooijer, J.G.; Zerom Godefay, D.

2000-01-01

Several nonparametric predictors based on the Nadaraya-Watson kernel regression estimator have been proposed in the literature. They include the conditional mean, the conditional median, and the conditional mode. In this paper, we consider three types of predictive regions for these predictors — the

Observed changes in seasonal heat waves and warm temperature extremes in the Romanian Carpathians

Science.gov (United States)

Micu, Dana; Birsan, Marius-Victor; Dumitrescu, Alexandru; Cheval, Sorin

2015-04-01

Extreme high temperature have a large impact on environment and human activities, especially in high elevation areas particularly sensitive to the recent climate warming. The climate of the Romanian Carpathians became warmer particularly in winter, spring and summer, exibiting a significant increasing frequency of warm extremes. The paper investigates the seasonal changes in the frequency, duration and intensity of heat waves in relation to the shifts in the daily distribution of maximum temperatures over a 50-year period of meteorological observations (1961-2010). The paper uses the heat wave definition recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) and exploits the gridded daily dataset of maximum temperature at 0.1° resolution (~10 km) developed in the framework of the CarpatClim project (www.carpatclim.eu). The seasonal changes in heat waves behavior were identified using the Mann-Kendall non-parametric trend test. The results suggest an increase in heat wave frequency and a lengthening of intervals affected by warm temperature extremes all over the study region, which are explained by the shifts in the upper (extreme) tail of the daily maximum temperature distribution in most seasons. The trends are consistent across the region and are well correlated to the positive phases of the East Atlantic Oscillation. Our results are in good agreement with the previous temperature-related studies concerning the Carpathian region. This study was realized within the framework of the project GENCLIM, financed by UEFISCDI, code PN-II 151/2014.

Changes in the timing and magnitude of floods in Canada

International Nuclear Information System (INIS)

Cunderlik, J.M.; Ouarda, T.B.M.J.

2008-01-01

It is expected that the global climate change will have significant impacts on the regime of hydrologic extremes. An increase in both the frequency and magnitude of hydrologic extremes is anticipated in the near future. As a consequence, the design and operation of water resource systems will have to adapt to the changing regime of hydrologic extremes. This study explores trends in the timing and magnitude of floods in natural streamflow gauging stations in Canada. The seasonality of floods is analyzed and the selected streamflow stations grouped into five flood seasonality regions. A common 30-year long observation period from 1974 to 2003 is used in the analysis to eliminate the effect of hydro-climatic variability in the timing and magnitude of floods resulting from different observation periods. The timing of floods is described in terms of directional statistics. A method is developed for analyzing trends in directional dates of flood occurrence that is not affected by the choice of zero direction. The magnitude of floods is analyzed by the annual maximum and peak-over-threshold methods. Trends in the timing and magnitude of floods are identified in each flood seasonality region using the Mann-Kendall nonparametric test, with a modification for auto-correlated data. The results show a good correspondence between the identified flood seasonality regions and the main terrestrial zones in Canada. Significant changes in the timing and magnitude of floods are found in the flood seasonality regions. (author)

Spatial and Temporal Variability of Rainfall in the Gandaki River Basin of Nepal Himalaya

Directory of Open Access Journals (Sweden)

Jeeban Panthi

2015-03-01

Full Text Available Landslides, floods, and droughts are recurring natural disasters in Nepal related to too much or too little water. The summer monsoon contributes more than 80% of annual rainfall, and rainfall spatial and inter-annual variation is very high. The Gandaki River, one of the three major rivers of Nepal and one of the major tributaries of the Ganges River, covers all agro-ecological zones in the central part of Nepal. Time series tests were applied for different agro-ecological zones of the Gandaki River Basin (GRB for rainfall trends of four seasons (pre-monsoon, monsoon, post-monsoon and winter from 1981 to 2012. The non-parametric Mann-Kendall and Sen’s methods were used to determine the trends. Decadal anomalies relative to the long-term average were analyzed using the APHRODITE precipitation product. Trends in number of rainy days and timing of the monsoon were also analyzed. We found that the post-monsoon, pre-monsoon and winter rainfalls are decreasing significantly in most of the zones but monsoon rainfall is increasing throughout the basin. In the hill region, the annual rainfall is increasing but the rainy days do not show any trend. There is a tendency toward later departure of monsoon from Nepal, indicating an increase in its duration. These seasonally and topographically variable trends may have significant impacts for the agriculture and livestock smallholders that form the majority of the population in the GRB.

Nonparametric e-Mixture Estimation.

Science.gov (United States)

Takano, Ken; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

2016-12-01

This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these auxiliary distributions-in other words, approximating the target distribution in a subspace spanned by a set of auxiliary distributions. Mixture modeling is one of the simplest ways to integrate information from the target and auxiliary distributions in order to express the target distribution as accurately as possible. There are two typical mixtures in the context of information geometry: the [Formula: see text]- and [Formula: see text]-mixtures. The [Formula: see text]-mixture is applied in a variety of research fields because of the presence of the well-known expectation-maximazation algorithm for parameter estimation, whereas the [Formula: see text]-mixture is rarely used because of its difficulty of estimation, particularly for nonparametric models. The [Formula: see text]-mixture, however, is a well-tempered distribution that satisfies the principle of maximum entropy. To model a target distribution with scarce observations accurately, this letter proposes a novel framework for a nonparametric modeling of the [Formula: see text]-mixture and a geometrically inspired estimation algorithm. As numerical examples of the proposed framework, a transfer learning setup is considered. The experimental results show that this framework works well for three types of synthetic data sets, as well as an EEG real-world data set.

Screen Wars, Star Wars, and Sequels: Nonparametric Reanalysis of Movie Profitability

OpenAIRE

W. D. Walls

2012-01-01

In this paper we use nonparametric statistical tools to quantify motion-picture profit. We quantify the unconditional distribution of profit, the distribution of profit conditional on stars and sequels, and we also model the conditional expectation of movie profits using a non- parametric data-driven regression model. The flexibility of the non-parametric approach accommodates the full range of possible relationships among the variables without prior specification of a functional form, thereb...

Nonparametric predictive inference in reliability

International Nuclear Information System (INIS)

Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.

2002-01-01

We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere

Seasonal and annual precipitation time series trend analysis in North Carolina, United States

Science.gov (United States)

Sayemuzzaman, Mohammad; Jha, Manoj K.

2014-02-01

The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the

Nonparametric estimation in models for unobservable heterogeneity

OpenAIRE

Hohmann, Daniel

2014-01-01

Nonparametric models which allow for data with unobservable heterogeneity are studied. The first publication introduces new estimators and their asymptotic properties for conditional mixture models. The second publication considers estimation of a function from noisy observations of its Radon transform in a Gaussian white noise model.

Nonparametric estimation of location and scale parameters

KAUST Repository

Potgieter, C.J.; Lombard, F.

2012-01-01

Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal

A Bayesian Nonparametric Approach to Factor Analysis

DEFF Research Database (Denmark)

Piatek, Rémi; Papaspiliopoulos, Omiros

2018-01-01

This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

Panel data specifications in nonparametric kernel regression

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

Integrated analysis of present and future responses of precipitation over selected Greek areas with different climate conditions

Science.gov (United States)

Paparrizos, Spyridon; Maris, Fotios; Matzarakis, Andreas

2016-03-01

The assessment of future precipitation variations prevailing in an area is essential for the research regarding climate and climate change. The current paper focuses on 3 selected areas in Greece that present different climatic characteristics due to their location and aims to assess and compare the future variation of annual and seasonal precipitation. Future precipitation data from the ENSEMBLES anthropogenic climate-change (ACC) global simulations and the Climate version of the Local Model (CLM) were obtained and analyzed. The climate simulations were performed for the future periods 2021-2050 and 2071-2100 under the A1B and B1 scenarios. Mann-Kendall test was applied to investigate possible trends. Spatial distribution of precipitation was performed using a combination of dynamic and statistical downscaling techniques and Kriging method within ArcGIS 10.2.1. The results indicated that for both scenarios, reference periods and study areas, precipitation is expected to be critically decreased. Additionally, Mann-Kendall test application showed a strong downward trend for every study area. Furthermore, the decrease in precipitation for the Ardas River basin characterized by the continental climate will be tempered, while in the Sperchios River basin it will be smoother due to the influence of some minor climatic variations in the basins' springs in the highlands where milder conditions occur. Precipitation decrease in the Geropotamos River basin which is characterized by Mediterranean climate will be more vigorous. B1 scenario appeared more optimistic for the Ardas and Sperchios River basins, while in the Geropotamos River basin, both applied scenarios brought similar results, in terms of future precipitation response.

TENDÊNCIAS HIDROLÓGICAS NO ALTO CURSO DA BACIA HIDROGRÁFICA DO RIO UBERABA, EM MINAS GERAIS

Directory of Open Access Journals (Sweden)

Vítor de Oliveira Santos

2016-06-01

Full Text Available O aumento da demanda hídrica por parte das médias e grandes cidades brasileiras tem gerado preocupações no poder público quanto ao abastecimento urbano. Na contramão do aumento da demanda por água, os sistemas hídricos parecem não mais suprir as necessidades impostas pela sociedade, sobretudo nos períodos de estiagem. A bacia hidrográfica do rio Uberaba ilustra esse cenário pois vem sofrendo escassez hídrica desde o início dos anos 2000. Desde então percebe-se a realização de medidas urgentes como a transposição das águas do rio Claro para suprir a demanda hídrica da cidade de Uberaba, além da criação da Área de Proteção Ambiental – APA rio Uberaba. Este trabalho tem como objetivo central analisar estatisticamente, através de testes de tendência, séries históricas de vazão no âmbito do alto curso do rio Uberaba. Justifica-se a escolha do alto curso do referido rio como objeto de estudo o fato de o abastecimento público do município de Uberaba ser realizado dentro de seus limites. Como método utilizou-se os testes de regressão linear, Mann-Kendall, Mann-Kendall Sazonal, Curvatura de Sen e o teste de homogeneidade de Pettitt. Os resultados indicam paulatina redução das vazões de estiagem e ligeiro aumento das vazões máximas.

On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression.

Science.gov (United States)

Pan, Wei

2003-07-22

Recently a class of nonparametric statistical methods, including the empirical Bayes (EB) method, the significance analysis of microarray (SAM) method and the mixture model method (MMM), have been proposed to detect differential gene expression for replicated microarray experiments conducted under two conditions. All the methods depend on constructing a test statistic Z and a so-called null statistic z. The null statistic z is used to provide some reference distribution for Z such that statistical inference can be accomplished. A common way of constructing z is to apply Z to randomly permuted data. Here we point our that the distribution of z may not approximate the null distribution of Z well, leading to possibly too conservative inference. This observation may apply to other permutation-based nonparametric methods. We propose a new method of constructing a null statistic that aims to estimate the null distribution of a test statistic directly. Using simulated data and real data, we assess and compare the performance of the existing method and our new method when applied in EB, SAM and MMM. Some interesting findings on operating characteristics of EB, SAM and MMM are also reported. Finally, by combining the idea of SAM and MMM, we outline a simple nonparametric method based on the direct use of a test statistic and a null statistic.

Nonparametric Analyses of Log-Periodic Precursors to Financial Crashes

Science.gov (United States)

Zhou, Wei-Xing; Sornette, Didier

We apply two nonparametric methods to further test the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The term "parametric" refers here to the use of the log-periodic power law formula to fit the data; in contrast, "nonparametric" refers to the use of general tools such as Fourier transform, and in the present case the Hilbert transform and the so-called (H, q)-analysis. The analysis using the (H, q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln(tc-t) variable, where tc is the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05 corresponding to the scaling ratio λ=2.67±0.12. These values are in very good agreement with those obtained in earlier works with different parametric techniques. This note is extracted from a long unpublished report with 58 figures available at , which extensively describes the evidence we have accumulated on these seven time series, in particular by presenting all relevant details so that the reader can judge for himself or herself the validity and robustness of the results.

Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment

DEFF Research Database (Denmark)

Christensen, Kim; Hounyo, Ulrich; Podolskij, Mark

In this paper, we propose a nonparametric way to test the hypothesis that time-variation in intraday volatility is caused solely by a deterministic and recurrent diurnal pattern. We assume that noisy high-frequency data from a discretely sampled jump-diffusion process are available. The test...... inference, we propose a new bootstrap approach, which leads to almost correctly sized tests of the null hypothesis. We apply the developed framework to a large cross-section of equity high-frequency data and find that the diurnal pattern accounts for a rather significant fraction of intraday variation...

Mobile Romberg test assessment (mRomberg).

Science.gov (United States)

Galán-Mercant, Alejandro; Cuesta-Vargas, Antonio I

2014-09-12

The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance. This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann-Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups. The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.

Examples of the Application of Nonparametric Information Geometry to Statistical Physics

Directory of Open Access Journals (Sweden)

Giovanni Pistone

2013-09-01

Full Text Available We review a nonparametric version of Amari’s information geometry in which the set of positive probability densities on a given sample space is endowed with an atlas of charts to form a differentiable manifold modeled on Orlicz Banach spaces. This nonparametric setting is used to discuss the setting of typical problems in machine learning and statistical physics, such as black-box optimization, Kullback-Leibler divergence, Boltzmann-Gibbs entropy and the Boltzmann equation.

Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

OpenAIRE

Hiroyuki Kasahara; Katsumi Shimotsu

2006-01-01

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

Escalas temporais e tendências observadas nas temperaturas m áximas no Estado do Ceará Timescales and observed trends in the highest temperatures in the state of Ceará

OpenAIRE

Costa, Iuri Moreira; UFC Campus Cariri; Mateus, Antonio Edgar; UFC Campus Cariri; Da Silva, Djane Fonseca; UFC Campus Cariri

2014-01-01

Pretendeu-se por meio das análises de ondeletas, identificar quais as possíveiscausas para a variabilidade na temperatura máxima do Ceará e com auxílio do teste de Mann-Kendall, verificou-se se há tendências de aumento ou diminuição dessa variável. Foram usados dados de temperatura máxima do INMET para o período de 1973-2010. Verificou-se que as regiões do estado do Ceará sofrem influencia das variações das escalas sazonais, interanuais e decadais sob suas temperaturas. As escalas sazonal, li...

Tendências de temperaturas mínimas e máximas do ar no Estado de Minas Gerais

OpenAIRE

Ávila, Léo Fernandes; Mello, Carlos Rogério de; Yanagi, Silvia de Nazaré Monteiro; Sacramento Neto, Olívio Bahia

2014-01-01

O objetivo deste trabalho foi avaliar tendências das temperaturas mínimas e máximas no Estado de Minas Gerais. Foram avaliados dados de 43 municípios, tendo-se considerado as escalas anual e sazonal - janeiro, abril, julho e outubro, que representam os meses centrais de verão, outono, inverno e primavera, respectivamente. Séries históricas de temperaturas mínimas e máximas do ar diárias, com extensão mínima de 30 anos, foram analisadas com base no teste de Mann-Kendall e no uso de regressão l...

Nonparametric predictive inference in statistical process control

NARCIS (Netherlands)

Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

2004-01-01

Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric

Non-parametric smoothing of experimental data

International Nuclear Information System (INIS)

Kuketayev, A.T.; Pen'kov, F.M.

2007-01-01

Full text: Rapid processing of experimental data samples in nuclear physics often requires differentiation in order to find extrema. Therefore, even at the preliminary stage of data analysis, a range of noise reduction methods are used to smooth experimental data. There are many non-parametric smoothing techniques: interval averages, moving averages, exponential smoothing, etc. Nevertheless, it is more common to use a priori information about the behavior of the experimental curve in order to construct smoothing schemes based on the least squares techniques. The latter methodology's advantage is that the area under the curve can be preserved, which is equivalent to conservation of total speed of counting. The disadvantages of this approach include the lack of a priori information. For example, very often the sums of undifferentiated (by a detector) peaks are replaced with one peak during the processing of data, introducing uncontrolled errors in the determination of the physical quantities. The problem is solvable only by having experienced personnel, whose skills are much greater than the challenge. We propose a set of non-parametric techniques, which allows the use of any additional information on the nature of experimental dependence. The method is based on a construction of a functional, which includes both experimental data and a priori information. Minimum of this functional is reached on a non-parametric smoothed curve. Euler (Lagrange) differential equations are constructed for these curves; then their solutions are obtained analytically or numerically. The proposed approach allows for automated processing of nuclear physics data, eliminating the need for highly skilled laboratory personnel. Pursuant to the proposed approach is the possibility to obtain smoothing curves in a given confidence interval, e.g. according to the χ 2 distribution. This approach is applicable when constructing smooth solutions of ill-posed problems, in particular when solving

Nonparametric Bayesian density estimation on manifolds with applications to planar shapes.

Science.gov (United States)

Bhattacharya, Abhishek; Dunson, David B

2010-12-01

Statistical analysis on landmark-based shape spaces has diverse applications in morphometrics, medical diagnostics, machine vision and other areas. These shape spaces are non-Euclidean quotient manifolds. To conduct nonparametric inferences, one may define notions of centre and spread on this manifold and work with their estimates. However, it is useful to consider full likelihood-based methods, which allow nonparametric estimation of the probability density. This article proposes a broad class of mixture models constructed using suitable kernels on a general compact metric space and then on the planar shape space in particular. Following a Bayesian approach with a nonparametric prior on the mixing distribution, conditions are obtained under which the Kullback-Leibler property holds, implying large support and weak posterior consistency. Gibbs sampling methods are developed for posterior computation, and the methods are applied to problems in density estimation and classification with shape-based predictors. Simulation studies show improved estimation performance relative to existing approaches.

Anton Grams dem Gustav Friedrich Wilhelm Großmann: Mozart schreibe eine neue Oper

Czech Academy of Sciences Publication Activity Database

Jonášová, Milada

2016-01-01

Roč. 53, č. 1 (2016), s. 29-53 ISSN 0018-7003 R&D Projects: GA ČR GAP409/12/2563 Institutional support: RVO:68378076 Keywords : Mozart * 1786 * letter * Anton Grams * Gustav Friedrich Wilhelm Großmann Subject RIV: AL - Art, Architecture, Cultural Heritage

Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas

Science.gov (United States)

Clark, Allan K.; Robert R. Morris,

2015-01-01

This report describes the geology and hydrostratigraphy of the Edwards and Trinity Groups in the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas. The hydrostratigraphy was defined based on variations in the amount and type of porosity of each lithostratigraphic unit, which varies depending on the unit’s original depositional environment, lithology, structural history, and diagenesis.

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

Science.gov (United States)

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

Smooth semi-nonparametric (SNP) estimation of the cumulative incidence function.

Science.gov (United States)

Duc, Anh Nguyen; Wolbers, Marcel

2017-08-15

This paper presents a novel approach to estimation of the cumulative incidence function in the presence of competing risks. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and the time to the event. The time to event distributions conditional on the event type are modeled using smooth semi-nonparametric densities. One strength of this approach is that it can handle arbitrary censoring and truncation while relying on mild parametric assumptions. A stepwise forward algorithm for model estimation and adaptive selection of smooth semi-nonparametric polynomial degrees is presented, implemented in the statistical software R, evaluated in a sequence of simulation studies, and applied to data from a clinical trial in cryptococcal meningitis. The simulations demonstrate that the proposed method frequently outperforms both parametric and nonparametric alternatives. They also support the use of 'ad hoc' asymptotic inference to derive confidence intervals. An extension to regression modeling is also presented, and its potential and challenges are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Investigation of MLE in nonparametric estimation methods of reliability function

International Nuclear Information System (INIS)

Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo

2001-01-01

There have been lots of trials to estimate a reliability function. In the ESReDA 20 th seminar, a new method in nonparametric way was proposed. The major point of that paper is how to use censored data efficiently. Generally there are three kinds of approach to estimate a reliability function in nonparametric way, i.e., Reduced Sample Method, Actuarial Method and Product-Limit (PL) Method. The above three methods have some limits. So we suggest an advanced method that reflects censored information more efficiently. In many instances there will be a unique maximum likelihood estimator (MLE) of an unknown parameter, and often it may be obtained by the process of differentiation. It is well known that the three methods generally used to estimate a reliability function in nonparametric way have maximum likelihood estimators that are uniquely exist. So, MLE of the new method is derived in this study. The procedure to calculate a MLE is similar just like that of PL-estimator. The difference of the two is that in the new method, the mass (or weight) of each has an influence of the others but the mass in PL-estimator not

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

Science.gov (United States)

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

Nonparametric estimation for censored mixture data with application to the Cooperative Huntington's Observational Research Trial.

Science.gov (United States)

Wang, Yuanjia; Garcia, Tanya P; Ma, Yanyuan

2012-01-01

This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington's Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways

Science.gov (United States)

Aghakhani Afshar, A.; Hasanzadeh, Y.; Besalatpour, A. A.; Pourreza-Bilondi, M.

2017-07-01

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992-2005, four evaluation criteria including Nash-Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R 2) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006-2037; mid-century, 2037-2070; and late-century, 2070-2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann-Kendall non-parametric test (MK) was also employed. The results of Mann-Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had

The nonparametric bootstrap for the current status model

NARCIS (Netherlands)

Groeneboom, P.; Hendrickx, K.

2017-01-01

It has been proved that direct bootstrapping of the nonparametric maximum likelihood estimator (MLE) of the distribution function in the current status model leads to inconsistent confidence intervals. We show that bootstrapping of functionals of the MLE can however be used to produce valid

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

Science.gov (United States)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

Directory of Open Access Journals (Sweden)

Biqing Cai

2015-04-01

Full Text Available This paper discusses nonparametric kernel regression with the regressor being a \\(d\\-dimensional \\(\\beta\\-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \\(\\sqrt{n(Th^{d}}\\, where \\(n(T\\ is the number of regenerations for a \\(\\beta\\-null recurrent process and the limiting distribution (with proper normalization is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent. The finite sample performance of the estimate is quite reasonable when the leave-one-out cross validation method is used for bandwidth selection. We apply the proposed method to study the relationship of Federal funds rate with 3-month and 5-year T-bill rates and discover the existence of nonlinearity of the relationship. Furthermore, the in-sample and out-of-sample performance of the nonparametric model is far better than the linear model.

A Bayesian nonparametric estimation of distributions and quantiles

International Nuclear Information System (INIS)

Poern, K.

1988-11-01

The report describes a Bayesian, nonparametric method for the estimation of a distribution function and its quantiles. The method, presupposing random sampling, is nonparametric, so the user has to specify a prior distribution on a space of distributions (and not on a parameter space). In the current application, where the method is used to estimate the uncertainty of a parametric calculational model, the Dirichlet prior distribution is to a large extent determined by the first batch of Monte Carlo-realizations. In this case the results of the estimation technique is very similar to the conventional empirical distribution function. The resulting posterior distribution is also Dirichlet, and thus facilitates the determination of probability (confidence) intervals at any given point in the space of interest. Another advantage is that also the posterior distribution of a specified quantitle can be derived and utilized to determine a probability interval for that quantile. The method was devised for use in the PROPER code package for uncertainty and sensitivity analysis. (orig.)

NParCov3: A SAS/IML Macro for Nonparametric Randomization-Based Analysis of Covariance

Directory of Open Access Journals (Sweden)

Richard C. Zink

2012-07-01

Full Text Available Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is a reduction of variance for the treatment effect which provides more powerful statistical tests and more precise confidence intervals. Second, it provides estimates of the treatment effect which are adjusted for random imbalances of covariates between the treatment groups. The nonparametric analysis of covariance method of Koch, Tangen, Jung, and Amara (1998 defines a very general methodology using weighted least-squares to generate covariate-adjusted treatment effects with minimal assumptions. This methodology is general in its applicability to a variety of outcomes, whether continuous, binary, ordinal, incidence density or time-to-event. Further, its use has been illustrated in many clinical trial settings, such as multi-center, dose-response and non-inferiority trials.NParCov3 is a SAS/IML macro written to conduct the nonparametric randomization-based covariance analyses of Koch et al. (1998. The software can analyze a variety of outcomes and can account for stratification. Data from multiple clinical trials will be used for illustration.

Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure

DEFF Research Database (Denmark)

Effraimidis, Georgios; Dahl, Christian Møller

In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric...

Elements of cultural continuity in modern German literature : a study of Goethe, Nietzsche and Mann

NARCIS (Netherlands)

Simuţ, R.

2010-01-01

This dissertation renders in a thematic and chronological line the argument o a Goethean influence concerning the way Nietzsche and Mann understood their position within German culture and reacted to the social and political perspective of their contemporaries. It outlines specific concepts and

Quantifying the anthropogenic and climatic contributions to changes in water discharge and sediment load into the sea: A case study of the Yangtze River, China.

Science.gov (United States)

Zhao, Yifei; Zou, Xinqing; Gao, Jianhua; Xu, Xinwanghao; Wang, Chenglong; Tang, Dehao; Wang, Teng; Wu, Xiaowei

2015-12-01

Based on data from the Datong hydrological station and 147 meteorological stations, the influences of climate change and human activities on temporal changes in water discharge and sediment load were examined in the Yangtze River basin from 1953 to 2010. The Mann-Kendall test, abrupt change test (Mann-Kendall and cumulative anomaly test), and Morlet wavelet method were employed to analyze the water discharge and sediment load data measured at the Datong hydrological station. The results indicated that the annual mean precipitation and water discharge exhibited decreasing trends of -0.0064 mm/10 yr and -1.41×10(8) m3/yr, respectively, and that the water sediment load showed a significant decreasing trend of -46.5×10(6) t/yr. Meanwhile, an abrupt change in the water discharge occurred in 2003. The sediment load also exhibited an abrupt change in 1985. From 1970 to 2010, the climate change and human activities contributed 72% and 28%, respectively, to the water discharge reduction. The human-induced decrease in the sediment load was 914.03×10(6) t/yr during the 1970s and 3301.79×10(6) t/yr during the 2000s. The contribution from human activities also increased from 71% to 92%, especially in the 1990s, when the value increased to 92%. Climate change and human activities contributed 14% and 86%, respectively, to the sediment load reduction. Inter-annual variations in water discharge and sediment load were affected by climate oscillations and human activities. The effect of human activities on the sediment load was considerably greater than those on water discharge in the Yangtze River basin. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate Change Assessments for Lakes Region of Turkey

Directory of Open Access Journals (Sweden)

Ayten Erol

2012-07-01

Full Text Available Climate change is one of the most important challenges for forestry. Forests are known to be most efficient natural tools to ensure availability and quality of water in many regions. Besides, planning of forest resources towards water quality and quantity is essential in countries that are expected to face with more frequent drought periods in the next decades due to climate change. Watershed management concept has been supposed as the primary tool to plan natural resources in a more efficient and sustainable way by both academicians and practitioners to mitigate and adapt climate change. Forest cover among other land use types provides the best regulating mechanism to mitigate erosion, sedimentation, desertification, and pollution. In addition, climate change can potentially affect forest stand dynamics by influencing the availability of water resources. Therefore, the amount of forest cover in a watershed is an indicator of climate change mitigation and adaptation. Climate change is a concern and risk for the sustainability of water resources in Lakes Region of Turkey. The objective of this study is to make a comprehensive assessment in lake watersheds of the Lakes region considering the forest cover. For this purpose, the study gives a general view of trends in climatic parameters using Mann Kendall trend test. The results showed that Mann Kendall trend test for temperature and precipitation data is not enough to evaluate the magnitude of potential changes of climate in terms of forest cover. Understanding impacts of changes in temperature and precipitation on forest cover, runoff data should be evaluated with temperature and precipitation for watersheds of forest areas in Lakes Region.

TEMPERATURE AND PRECIPITATION CHANGES IN TÂRGU-MURES (ROMANIA FROM PERIOD 1951-2010

Directory of Open Access Journals (Sweden)

O.Rusz

2012-03-01

Full Text Available Temperature and precipitation changes in Târgu Mures (Romania from period 1951-2010. The analysis was made based upon meteorological data collected at Târgu Mures meteorological station (Romania, Mures county, lat. 46°32’N, lon. 24°32’E, elevation 308 m, between 1951 and 2010. Several climatic parameters were studied (for instance, annual and monthly mean temperature, maximum precipitation in 24 hours, number of summer days, etc. Detected inhomogeneities are not related to instrumental causes or geographical relocation. Positive and statistical significant trends (Mann-Kendall test are indicated for: mean annual temperatures, mean temperatures of warm months, average of the maximum and minimum temperatures (annual and warm months data, number of days with mean temperature between 20.1-25.0 °C, number of days with precipitation ≥0 mm, and for all parameters of precipitation of September. The sequential version of Mann-Kendall test show a beginning of a trend in 1956 in the case of mean temperature (at same, the two and three parts regression denote this year like a moment of change, years 1965 and 1992 in the case of annual amount of precipitation. CUSUM charts indicate occurs of changes points at 1988, 2005, 2009 (mean temperature respectively at 1989, 2004 (precipitation, and at 1968, 1992 (daily temperature range. Tendencies of overlapped time series reveal a more important increase at the end of period (mainly for mean temperature. The analysis with RClimDex show for 5 extreme climate indices a significant trend: positive for summer days, warm nights, warm spell duration indicator and negative for cold nights and cold days.

Regional precipitation trend analysis at the Langat River Basin, Selangor, Malaysia

Science.gov (United States)

Palizdan, Narges; Falamarzi, Yashar; Huang, Yuk Feng; Lee, Teang Shui; Ghazali, Abdul Halim

2014-08-01

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982-2011 were examined at the 95 % level of significance using the regional average Mann-Kendall (RAMK) test and the regional average Mann-Kendall coupled with bootstrap (RAMK-bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km × 5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.

Exploring spatial-temporal dynamics of fire regime features in mainland Spain

Science.gov (United States)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

Statistical analysis of the electric energy production from photovoltaic conversion using mobile and fixed constructions

Science.gov (United States)

Bugała, Artur; Bednarek, Karol; Kasprzyk, Leszek; Tomczewski, Andrzej

2017-10-01

The paper presents the most representative - from the three-year measurement time period - characteristics of daily and monthly electricity production from a photovoltaic conversion using modules installed in a fixed and 2-axis tracking construction. Results are presented for selected summer, autumn, spring and winter days. Analyzed measuring stand is located on the roof of the Faculty of Electrical Engineering Poznan University of Technology building. The basic parameters of the statistical analysis like mean value, standard deviation, skewness, kurtosis, median, range, or coefficient of variation were used. It was found that the asymmetry factor can be useful in the analysis of the daily electricity production from a photovoltaic conversion. In order to determine the repeatability of monthly electricity production, occurring between the summer, and summer and winter months, a non-parametric Mann-Whitney U test was used as a statistical solution. In order to analyze the repeatability of daily peak hours, describing the largest value of the hourly electricity production, a non-parametric Kruskal-Wallis test was applied as an extension of the Mann-Whitney U test. Based on the analysis of the electric energy distribution from a prepared monitoring system it was found that traditional forecasting methods of the electricity production from a photovoltaic conversion, like multiple regression models, should not be the preferred methods of the analysis.

The Parallel Lives of Lukács and Thomas Mann: from romanticism of disillusionment to committed humanism

Directory of Open Access Journals (Sweden)

Kaio Felipe

2013-06-01

Full Text Available This paper aims to show the artistic and philosophical dialogue developed over the first half of the 20th Century between the Hungarian thinker Georg Lukács and the German writer Thomas Mann. From an approach inspired by the sociology of knowledge from Mannheim and the historical emphasis on the individuality from Burckhardt, I will work in three dimensions: first, the paths of both intellectual and moments where they intersect, and secondly, the inspiration that messianism Lukács gave for the construction of the controversial character Leo Naphta's novel “The Magic Mountain”, Mann; thirdly, about how the fictional work this was interpreted by the Hungarian literary criticism.

Bayesian Non-Parametric Mixtures of GARCH(1,1 Models

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John W. Lau

2012-01-01

Full Text Available Traditional GARCH models describe volatility levels that evolve smoothly over time, generated by a single GARCH regime. However, nonstationary time series data may exhibit abrupt changes in volatility, suggesting changes in the underlying GARCH regimes. Further, the number and times of regime changes are not always obvious. This article outlines a nonparametric mixture of GARCH models that is able to estimate the number and time of volatility regime changes by mixing over the Poisson-Kingman process. The process is a generalisation of the Dirichlet process typically used in nonparametric models for time-dependent data provides a richer clustering structure, and its application to time series data is novel. Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. The methodology is illustrated on the Standard and Poor's 500 financial index.

Single versus mixture Weibull distributions for nonparametric satellite reliability

International Nuclear Information System (INIS)

Castet, Jean-Francois; Saleh, Joseph H.

2010-01-01

Long recognized as a critical design attribute for space systems, satellite reliability has not yet received the proper attention as limited on-orbit failure data and statistical analyses can be found in the technical literature. To fill this gap, we recently conducted a nonparametric analysis of satellite reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we provide an advanced parametric fit, based on mixture of Weibull distributions, and compare it with the single Weibull distribution model obtained with the Maximum Likelihood Estimation (MLE) method. We demonstrate that both parametric fits are good approximations of the nonparametric satellite reliability, but that the mixture Weibull distribution provides significant accuracy in capturing all the failure trends in the failure data, as evidenced by the analysis of the residuals and their quasi-normal dispersion.

Modern nonparametric, robust and multivariate methods festschrift in honour of Hannu Oja

CERN Document Server

Taskinen, Sara

2015-01-01

Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

"German Culture is where I am": Thomas Mann in Exile

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Helmut Koopmann

1982-09-01

Full Text Available Thomas Mann in exile reacted like many writers expelled from Germany: totally irritated he tried to defend his own identity by claiming that he was still the leading representative of Germany. But about 1938 a process of dissociation from Germany started which led to sharp remarks on Germany in his The Beloved Returns , to his conviction that German culture was where he lived and to the acknowledgement of America as his new home. Traces of his experience of exile, and a late answer on his separation from Germany in 1933, however, are to be found even in his incompleted novel Felix Krull which seems to have turned the disgusting experience of exile into friendly mythological light.

Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

NARCIS (Netherlands)

Kuosmanen, T.K.

2005-01-01

Environmental Economics and Natural Resources Group at Wageningen University in The Netherlands Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion.

Nonparametric estimation for censored mixture data with application to the Cooperative Huntington’s Observational Research Trial

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Wang, Yuanjia; Garcia, Tanya P.; Ma, Yanyuan

2012-01-01

This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington’s Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

Variability of extreme wet events over Malawi

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Libanda Brigadier

2017-01-01

Full Text Available Adverse effects of extreme wet events are well documented by several studies around the world. These effects are exacerbated in developing countries like Malawi that have insufficient risk reduction strategies and capacity to cope with extreme wet weather. Ardent monitoring of the variability of extreme wet events over Malawi is therefore imperative. The use of the Expert Team on Climate Change Detection and Indices (ETCCDI has been recommended by many studies as an effective way of quantifying extreme wet events. In this study, ETCCDI indices were used to examine the number of heavy, very heavy, and extremely heavy rainfall days; daily and five-day maximum rainfall; very wet and extremely wet days; annual wet days and simple daily intensity. The Standard Normal Homogeneity Test (SNHT was employed at 5% significance level before any statistical test was done. Trend analysis was done using the nonparametric Mann-Kendall statistical test. All stations were found to be homogeneous apart from Mimosa. Trend results show high temporal and spatial variability with the only significant results being: increase in daily maximum rainfall (Rx1day over Karonga and Bvumbwe, increase in five-day maximum rainfall (Rx5day over Bvumbwe. Mzimba and Chileka recorded a significant decrease in very wet days (R95p while a significant increase was observed over Thyolo. Chileka was the only station which observed a significant trend (decrease in extremely wet rainfall (R99p. Mzimba was the only station that reported a significant trend (decrease in annual wet-day rainfall total (PRCPTOT and Thyolo was the only station that reported a significant trend (increase in simple daily intensity (SDII. Furthermore, the findings of this study revealed that, during wet years, Malawi is characterised by an anomalous convergence of strong south-easterly and north-easterly winds. This convergence is the main rain bringing mechanism to Malawi.

The Diversity of Vibrios Associated with Vibriosis in Pacific White Shrimp (Litopenaeus vannamei) from Extensive Shrimp Pond in Kendal District, Indonesia

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Sarjito; Harjuno Condro Haditomo, Alfabetian; Desrina; Djunaedi, Ali; Budi Prayitno, Slamet

2018-02-01

Vibriosis out breaks frequently occur in extensive shrimps farming. The study were commenced to find out the clinical signs of white shrimp that was infected by the Vibrio and to identify the bacterial associated with vibriosis in the pacific white shrimp, Litopenaeus vannamei. Bacterial isolates were gained from hepatopancreas and telson of moribund shrimps that were collected from extensive shrimp ponds of Kendal District, Indonesia and cultured on Thiosulfate Citrate Bile Salts Sucrose Agar (TCBSA). Isolates were clustered and identified using repetitive sequence-based polymerase chain reaction (rep-PCR). Three representative isolates (SJV 03, SJV 05 and SJV 19) were amplified with PCR using primers for 16S rRNA, and sequence for further identification. The clinical signs of shrimps affected by vibrio were pale hepatopancreas, weak of telson, dark and reddish coloration of smouth, patches of red colour in part of the body on the carapace, periopods, pleuopods, and telson. A total of 19 isolates were obtained and belong to three groups of genus Vibrios. Result of the 16S DNA sequence analysis, the vibrio found in this study related to vibriosis in white shrimps from extensive shrimp ponds of Kendal were closely related to Vibrio harveyi (SJV 03); V. parahaemolyticus (SJV 05) and V. alginolyticus (SJV 19).

Trends in total rainfall, heavy rain events, and number of dry days in San Juan, Puerto Rico, 1955-2009

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Pablo A. Méndez-Lázaro

2014-06-01

Full Text Available Climate variability is a threat to water resources on a global scale and in tropical regions in particular. Rainfall events and patterns are associated worldwide with natural disasters like mudslides and landslides, meteorological phenomena like hurricanes, risks/hazards including severe storms and flooding, and health effects like vector-borne and waterborne diseases. Therefore, in the context of global change, research on rainfall patterns and their variations presents a challenge to the scientific community. The main objective of this research was to analyze recent trends in precipitation in the San Juan metropolitan area in Puerto Rico and their relationship with regional and global climate variations. The statistical trend analysis of precipitation was performed with the nonparametric Mann-Kendall test. All stations showed positive trends of increasing annual rainfall between 1955 and 2009. The winter months of January and February had an increase in monthly rainfall, although winter is normally a dry season on the island. Regarding dry days, we found an annual decreasing trend, also specifically in winter. In terms of numbers of severe rainfall events described as more than 78 mm in 24 hours, 63 episodes have occurred in the San Juan area in the last decade, specifically in the 2000-2009 time frame, with an average of 6 severe events per year. The majority of the episodes occurred in summer, more frequently in August and September. These results can be seen as a clear example of the complexity of spatial and temporal of rainfall distribution over a tropical city.

Chronic groundwater decline: A multi-decadal analysis of groundwater trends under extreme climate cycles

Science.gov (United States)

Le Brocque, Andrew F.; Kath, Jarrod; Reardon-Smith, Kathryn

2018-06-01

Chronic groundwater decline is a concern in many of the world's major agricultural areas. However, a general lack of accurate long-term in situ measurement of groundwater depth and analysis of trends prevents understanding of the dynamics of these systems at landscape scales. This is particularly worrying in the context of future climate uncertainties. This study examines long-term groundwater responses to climate variability in a major agricultural production landscape in southern Queensland, Australia. Based on records for 381 groundwater bores, we used a modified Mann-Kendall non-parametric test and Sen's slope estimator to determine groundwater trends across a 26-year period (1989-2015) and in distinct wet and dry climatic phases. Comparison of trends between climatic phases showed groundwater level recovery during wet phases was insufficient to offset the decline in groundwater level from the previous dry phase. Across the entire 26-year sampling period, groundwater bore levels (all bores) showed an overall significant declining trend (p 0.05). Spatially, both declining and rising bores were highly clustered. We conclude that over 1989-2015 there is a significant net decline in groundwater levels driven by a smaller subset of highly responsive bores in high irrigation areas within the catchment. Despite a number of targeted policy interventions, chronic groundwater decline remains evident in the catchment. We argue that this is likely to continue and to occur more widely under potential climate change and that policy makers, groundwater users and managers need to engage in planning to ensure the sustainability of this vital resource.

Prevailing trends of climatic extremes across Indus-Delta of Sindh-Pakistan

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Abbas, Farhat; Rehman, Iqra; Adrees, Muhammad; Ibrahim, Muhammad; Saleem, Farhan; Ali, Shafaqat; Rizwan, Muhammad; Salik, Muhammad Raza

2018-02-01

This study examines the variability and change in the patterns of climatic extremes experienced in Indus-Delta of Sindh province of Pakistan, comprising regions of Karachi, Badin, Mohenjodaro, and Rohri. The homogenized daily minimum and maximum temperature and precipitation data for a 36-year period were used to calculate 13 and 11 indices of temperature and precipitation extremes with the help of RClimDex, a program written in the statistical software package R. A non-parametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of the calculated trend. Temperatures of summer days and tropical nights increased in the region with overall significant warming trends for monthly maximum temperature as well as for warm days and nights reflecting dry conditions in the study area. The warm extremes and nighttime temperature indices showed greater trends than cold extremes and daytime indices depicting an overall warming trends in the Delta. Historic decrease in the acreage of major crops and over 33% decrease in agriculture credit for Sindh are the indicators of adverse impacts of warmer and drier weather on Sindh agriculture. Trends reported for Karachi and Badin are expected to decrease rice cultivation, hatching of fisheries, and mangroves forest surrounding these cities. Increase in the prevailing temperature trends will lead to increasingly hotter and drier summers resulting to constraints on cotton, wheat, and rice yield in Rohri and Mohenjodaro areas due to increased crop water requirements that may be met with additional groundwater pumping; nonetheless, the depleted groundwater resources would have a direct impact on the region's economy.

PENGARUH PELAYANAN, KINERJA PENGURUS KOPERASI, DAN MOTIVASI BERKOPERASI TERHADAP PARTISIPASI ANGGOTA KOPERASI PEGAWAI REPUBLIK INDONESIA (KPRI EKA KARYA KABUPATEN KENDAL

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Tri Yuni Sulistyowati

2015-06-01

Full Text Available Tujuan penelitian ini adalah untuk mengetahui pengaruh pelayanan, kinerja pengurus koperasi, dan motivasi berkoperasi terhadap partisipasi anggota Koperasi Pegawai Republik Indonesia (KPRI Eka Karya Kabupaten Kendal. Penelitian ini merupakan penelitian kuantitatif, dengan populasi berjumlah 496 anggota dengan sampel 83 anggota. Metode pengambilan data yang digunakan adalah kuesioner dan dokumentasi. Metode analisis data menggunakan analisis deskriptif, regresi linier berganda dan uji asumsi klasik. Hasil penelitian menunjukkan bahwa secara simultan terdapat pengaruh pelayanan, kinerja pengurus koperasi, dan motivasi berkoperasi terhadap partisipasi anggota sebesar 58,2%. Secara parsial pelayanan berpengaruh sebesar 7,1%, kinerja pengurus koperasi berpengaruh sebesar 3,3% dan motivasi berkoperasi berpengaruh sebesar 27%. Dengan pelayanan, kinerja pengurus koperasi, dan motivasi berkoperasi yang baik maka akan meningkatkan partisipasi anggota. The results showed the service, the performance of cooperative management and cooperative motivation affect the participation of members simultaneously by 58.2% while the rest is influenced by other variables not examined. Furthermore, the effect of partial services to the participation of members was 7.1%, the effect of partial performance of the cooperative board member participation was 3.3% and the effect of partial motivation for the participation of members of cooperatives was 27%. Suggestions for KPRI Eka Karya Kendal is to be improving as more responsive services tehadap complaints, better hygiene as well as expanding the cooperative store stores that optimal participation of more members.

Rank-based permutation approaches for non-parametric factorial designs.

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Umlauft, Maria; Konietschke, Frank; Pauly, Markus

2017-11-01

Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

Non-Parametric Analysis of Rating Transition and Default Data

DEFF Research Database (Denmark)

Fledelius, Peter; Lando, David; Perch Nielsen, Jens

2004-01-01

We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...

Adaptive nonparametric Bayesian inference using location-scale mixture priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2010-01-01

We study location-scale mixture priors for nonparametric statistical problems, including multivariate regression, density estimation and classification. We show that a rate-adaptive procedure can be obtained if the prior is properly constructed. In particular, we show that adaptation is achieved if

Non-parametric analysis of production efficiency of poultry egg ...

African Journals Online (AJOL)

Non-parametric analysis of production efficiency of poultry egg farmers in Delta ... analysis of factors affecting the output of poultry farmers showed that stock ... should be put in place for farmers to learn the best farm practices carried out on the ...

A Nonparametric Bayesian Approach For Emission Tomography Reconstruction

International Nuclear Information System (INIS)

Barat, Eric; Dautremer, Thomas

2007-01-01

We introduce a PET reconstruction algorithm following a nonparametric Bayesian (NPB) approach. In contrast with Expectation Maximization (EM), the proposed technique does not rely on any space discretization. Namely, the activity distribution--normalized emission intensity of the spatial poisson process--is considered as a spatial probability density and observations are the projections of random emissions whose distribution has to be estimated. This approach is nonparametric in the sense that the quantity of interest belongs to the set of probability measures on R k (for reconstruction in k-dimensions) and it is Bayesian in the sense that we define a prior directly on this spatial measure. In this context, we propose to model the nonparametric probability density as an infinite mixture of multivariate normal distributions. As a prior for this mixture we consider a Dirichlet Process Mixture (DPM) with a Normal-Inverse Wishart (NIW) model as base distribution of the Dirichlet Process. As in EM-family reconstruction, we use a data augmentation scheme where the set of hidden variables are the emission locations for each observed line of response in the continuous object space. Thanks to the data augmentation, we propose a Markov Chain Monte Carlo (MCMC) algorithm (Gibbs sampler) which is able to generate draws from the posterior distribution of the spatial intensity. A difference with EM is that one step of the Gibbs sampler corresponds to the generation of emission locations while only the expected number of emissions per pixel/voxel is used in EM. Another key difference is that the estimated spatial intensity is a continuous function such that there is no need to compute a projection matrix. Finally, draws from the intensity posterior distribution allow the estimation of posterior functionnals like the variance or confidence intervals. Results are presented for simulated data based on a 2D brain phantom and compared to Bayesian MAP-EM

Detecting gradual and abrupt changes in water quality time series in response to regional payment programs for watershed services in an agricultural area

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He, Tian; Lu, Yan; Cui, Yanping; Luo, Yabo; Wang, Min; Meng, Wei; Zhang, Kaijie; Zhao, Feifei

2015-06-01

Market-based watershed protection instruments can effectively improve water quality at various catchment scales. Two payments for watershed services (PWS) programs for water quality improvement have been successively implemented in the Huai River catchment and its sub-watershed, the Shaying River catchment, in Henan Province since 2009. To detect changes in water quality in response to PWS schemes, nonparametric statistical approaches were used to analyze gradual and abrupt trends in water quality, focusing on chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) at 26 monitoring stations in the Huai River watershed during 2006-2013. The nonparametric Mann-Kendall test and the Theil-Sen estimator were used to identify trends and their magnitudes in weekly water quality observations and the Pettitt test was applied to change-point analysis of water quality time series. We found decreasing concentration trends in the weekly water quality data set in this catchment, with water quality at most stations affected by the PWS schemes. The COD and NH3-N concentrations decreased at 26 stations by an average of 0.05 mg/L wk and 0.01 mg/L wk, respectively, from 2006 to 2013. Meanwhile, the mean concentrations of COD and NH3-N decreased at the 26 stations by an average of 18.03 mg/L and 4.82 mg/L, respectively, after the abrupt change points of the time-series trends of these two pollutants. We also estimated annual reductions in COD and NH3-N for each station based on average flow observations using the Theil-Sen approach along with the resulting economic benefits from 2009 to 2010. The COD and NH3-N reductions were 14604.50 and 6213.25 t/y, respectively, in the Huai River catchment in Henan Province. The total economic benefits of reductions in these two pollutants were 769.71 million ¥ in 2009 and 2010, accounting for 0.08% and 0.06%, respectively, of the GDP in the entire Huai River watershed of Henan Province. These results provide new insights into the linkages

International Conference on Robust Rank-Based and Nonparametric Methods

CERN Document Server

McKean, Joseph

2016-01-01

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

Bayesian nonparametric dictionary learning for compressed sensing MRI.

Science.gov (United States)

Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

2014-12-01

We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

PENINGKATAN PARTISIPASI DAN KETERAMPILAN SISWA MELALUI MODEL THINK PAIR SHARE PADA KOMPETENSI DASAR MEMBUKUKAN MUTASI DAN SELISIH DANA KAS KECIL DI SMK BHAKTI PERSADA KENDAL

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Wahibah Lana In Ma

2015-02-01

Full Text Available Subjek penelitian ini adalah siswa kelas XI Administrasi Perkantoran SMK Bhakti Persada Kendal. Rancangan penelitian ini merupakan penelitian tindakan kelas dengan tiga siklus, dimana setiap siklus meliputi perencanaan, pelaksanaan, pengamatan, dan refleksi. Metode pengumpulan data yang digunakan dalam penelitian ini adalah metode tes, observasi, dan dokumentasi. Metode analisis data dalam penelitian ini menggunakan analisis deskriptif..Hasil penelitian pada siklus I menunjukkan partisipasi siswa sebesar 65,50% dalam kategori cukup partisipatif, keterampilan siswa sebesar 68,38% dalam kategori cukup terampil, ketuntasan klasikal 65,50% dengan rata-rata hasil belajar 73,25. Untuk hasil penelitian siklus II menunjukkan partisipasi siswa sebesar 69% , keterampilan siswa sebesar 73,30%, ketuntasan klasikal 61,29%, menunjukkan rata-rata hasil belajar siswa sebesar 79,96. Untuk hasil penelitian siklus III menunjukkan partisipasi siswa sebesar 82,87%, keterampilan siswa sebesar 82,01%, ketuntasan klasikal 77,41% dengan rata-rata hasil belajar siswa sebesar 79,48. The subjects were students of class XI Administrative SMK Bhakti Persada Kendal. The design of this study is a class action with three cycles, where each cycle includes planning, implementation, observation, and reflection. Data collection methods used in this research is the method of testing, observation, and documentation. Data collection methods used in this research is the method of testing, observation, and documentation. Methods of data analysis in this research using descriptive analysis. The results of the study in the first cycle shows student participation of 65.50 % in the category of participatory enough, the skills students 68,38% in the category of skilled enoug, classical completeness 65.50% with an average of 73.25 learning outcomes. For the second cycle study results showed a 69% student participation, student skills at 73.30, 61.29% classical completeness, showed an average

An Examination of Cooper's Test for Monotonic Trend

Science.gov (United States)

Hsu, Louis

1977-01-01

A statistic for testing monotonic trend that has been presented in the literature is shown not to be the binomial random variable it is contended to be, but rather it is linearly related to Kendall's tau statistic. (JKS)

Modeling annual extreme temperature using generalized extreme value distribution: A case study in Malaysia

Science.gov (United States)

Hasan, Husna; Salam, Norfatin; Kassim, Suraiya

2013-04-01

Extreme temperature of several stations in Malaysia is modeled by fitting the annual maximum to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are used to detect stochastic trends among the stations. The Mann-Kendall (MK) test suggests a non-stationary model. Three models are considered for stations with trend and the Likelihood Ratio test is used to determine the best-fitting model. The results show that Subang and Bayan Lepas stations favour a model which is linear for the location parameters while Kota Kinabalu and Sibu stations are suitable with a model in the logarithm of the scale parameters. The return level is the level of events (maximum temperature) which is expected to be exceeded once, on average, in a given number of years, is obtained.

Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

Science.gov (United States)

Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

2015-01-01

Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

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Xin Tian

2017-06-01

Full Text Available We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online. Clustering is introduced for dictionary learning. A set of dictionaries could be generated, and each dictionary is used for one cluster’s sparse coding. In this way, the signals in one cluster could be well represented by their corresponding dictionaries. A nonparametric Bayesian dictionary learning method is used to learn the dictionaries, which naturally infers an appropriate dictionary size for each cluster. A uniform quantizer and an adaptive arithmetic coding algorithm are adopted to code the sparse coefficients. With comparisons to other state-of-the art approaches, the effectiveness of the proposed method could be validated in the experiments.

Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model

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Isaac Mugume

2016-01-01

Full Text Available Numerical models are presently applied in many fields for simulation and prediction, operation, or research. The output from these models normally has both systematic and random errors. The study compared January 2015 temperature data for Uganda as simulated using the Weather Research and Forecast model with actual observed station temperature data to analyze the bias using parametric (the root mean square error (RMSE, the mean absolute error (MAE, mean error (ME, skewness, and the bias easy estimate (BES and nonparametric (the sign test, STM methods. The RMSE normally overestimates the error compared to MAE. The RMSE and MAE are not sensitive to direction of bias. The ME gives both direction and magnitude of bias but can be distorted by extreme values while the BES is insensitive to extreme values. The STM is robust for giving the direction of bias; it is not sensitive to extreme values but it does not give the magnitude of bias. The graphical tools (such as time series and cumulative curves show the performance of the model with time. It is recommended to integrate parametric and nonparametric methods along with graphical methods for a comprehensive analysis of bias of a numerical model.

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

Science.gov (United States)

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

Decompounding random sums: A nonparametric approach

DEFF Research Database (Denmark)

Hansen, Martin Bøgsted; Pitts, Susan M.

Observations from sums of random variables with a random number of summands, known as random, compound or stopped sums arise within many areas of engineering and science. Quite often it is desirable to infer properties of the distribution of the terms in the random sum. In the present paper we...... review a number of applications and consider the nonlinear inverse problem of inferring the cumulative distribution function of the components in the random sum. We review the existing literature on non-parametric approaches to the problem. The models amenable to the analysis are generalized considerably...

Nonparametric modeling of dynamic functional connectivity in fmri data

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus

2015-01-01

dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...

Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

Czech Academy of Sciences Publication Activity Database

Kalina, Jan; Zvárová, Jana

2017-01-01

Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

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Ghosh, Debashis; Chinnaiyan, Arul M

2009-01-01

In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

Evaluation of Diode laser (940 nm irradiation effect on microleakage in class V composite restoration before and after adhesive application

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loghman rezaei

2018-03-01

Full Text Available Introduction: Nowadays, the main focus of dental studies is on adhesive dental materials; since clinical long-term success of bonded restorations depended more on marginal microleakage minimization. So, the aim of this study was Evaluation of Diode laser irradiation effect on microleakage in class V composite restoration before and after adhesive application. Materials and methods: In this in vitro-experimental study, standard class V cavity was prepared on lingual and buccal surfaces of 60 premolar teeth. For evaluation of microleakage, 60 teeth were divided randomly into four groups A, B, C, D (n=15: A primer + adhesive (Clearfil TM SE Bond, B primer + Diode laser + adhesive (940nm wave-length, 21J total energy, 0.7W power, 30s irradiation time C primer + adhesive + Diode laser D primer + Diode laser + adhesive + Diode laser. Then, restoration was completed by Z250 composite. For data analyzing, we used SPSS 16 software. For statistical analysis, we used Non-parametric Kruskal-Wallis & Mann-Whitney tests at 0.05% significance level.  Results: According to non-parametric Kruskal-Wallis test, microleakage scores had not significant difference before and after laser irradiation on gingival margins (p=0.116. But, in occlusal margins the results were significant among the groups (p=0.015. Also according to non-parametric Mann-Whitney tests among the occlusal microleakage scores, group B and D (Diode laser irradiation after primer and Diode laser irradiation after primer and adhesive showed significant results. Conclusion: This study findings showed that in 6th generation adhesives, Diode laser irradiation on self-etch primer before bonding have significant effect on reduction of occlusal marginal microleakage in class V cavities although there was no significant positive effect of Diode laser on gingival margins.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

Science.gov (United States)

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Predictors of Success in Bariatric Surgery: the Role of BMI and Pre-operative Comorbidities.

Science.gov (United States)

da Cruz, Magda Rosa Ramos; Branco-Filho, Alcides José; Zaparolli, Marília Rizzon; Wagner, Nathalia Farinha; de Paula Pinto, José Simão; Campos, Antônio Carlos Ligocki; Taconeli, Cesar Augusto

2017-11-10

This is a retrospective review of 204 patients who underwent bariatric surgery. The impact of weight regain (WR), pre-operative comorbidities and BMI values on the recurrence of comorbidities was evaluated, and an equation was elaborated to estimate BMI at 5 years of bariatric surgery. Pre-operative data, after 1 year and after 5 years, was collected from the medical records. Descriptive analyses and bivariate hypothesis tests were performed first, and then, a generalised linear regression model with Tweedie distribution was adjusted. The hit rate and the Kendall coefficient of concordance (Kendall's W) of the equation were calculated. At the end, the Mann-Whitney test was performed between the BMI, WR and the presence of comorbidities, after a post-operative period of 5 years. The adjustment of the model resulted in an equation that estimates the mean value of BMI 5 years after surgery. The hit rate was 82.35% and the value of Kendall's W was 0.85 for the equation. It was found that patients with comorbidities presented a higher median WR (10.13%) and a higher mean BMI (30.09 kg/m 2 ) 5 years after the surgery. It is concluded that the equation is useful for estimating the mean BMI at 5 years of surgery and that patients with low pre-operative HDL and folic acid levels, with depression and/or anxiety and a higher BMI, have a higher BMI at 5 years of surgery and higher incidence of comorbid return and dissatisfaction with post-operative results.

VARIABILIDADE DAS CHUVAS NA VERTENTE PARANAENSE DA BACIA DO RIO PARANAPANEMA - 1999-2000 A 2009-2010

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Vinicius Carmello

2015-06-01

Full Text Available Os investimentos no campo vêm sendo ampliados ao longo das últimas décadas, sobretudo pela justificativa de se minimizar as repercussões, ditas “naturais”, no território agrícola ocupado. O objetivo deste artigo é analisar a variabilidade das chuvas na vertente paranaense da bacia do rio Paranapanema em período de safra de soja (outubro – abril. Para tanto, foram aplicadas duas técnicas estatísticas: Mann-Kendall e Percentil, com o intuito de estudar a tendência e a variabilidade dos totais anuais de chuva da série histórica entre os anos 1999-2000 a 2009-2010. Para isso utilizou-se dados de precipitação de 89 postos pluviométricos administrados pelo Instituto das Águas do Paraná. Ademais, definiram-se períodos extremamente secos, secos, habituais, chuvosos e extremamente chuvosos, representados em um painel tempo-espacial. Quanto ao teste de Mann-Kendall: 13 postos pluviométricos apresentaram tendência positiva de aumento das chuvas. No que se refere aos resultados mais expressivos relacionados à variabilidade da chuva anual acumulada, concluiu-se que o ano agrícola de 1999–2000 foi definido como padrão seco, em contraposição ao ano agrícola chuvoso de 2009–2010. Os valores de produtividade de soja utilizados para medir o impacto desses períodos extremos também evidenciam variações em resposta aos registros pluviométricos de cada ano.

Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

Science.gov (United States)

Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

Nonparametric Mixture of Regression Models.

Science.gov (United States)

Huang, Mian; Li, Runze; Wang, Shaoli

2013-07-01

Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

Science.gov (United States)

Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

For whom the bells toll: a polyphonic fragment in Thomas Mann's 'Der Erwählte'

NARCIS (Netherlands)

Lichtenstein, S.

2010-01-01

Although many studies have been devoted to the role of music in the works of Thomas Mann, very little attention has been paid to this aspect in his novel Der Erwählte. This novel presents two main ideas, an ethical and an aesthetical one, which are connected with each other and with Mann’s critical

On the robust nonparametric regression estimation for a functional regressor

OpenAIRE

Azzedine , Nadjia; Laksaci , Ali; Ould-Saïd , Elias

2009-01-01

On the robust nonparametric regression estimation for a functional regressor correspondance: Corresponding author. (Ould-Said, Elias) (Azzedine, Nadjia) (Laksaci, Ali) (Ould-Said, Elias) Departement de Mathematiques--> , Univ. Djillali Liabes--> , BP 89--> , 22000 Sidi Bel Abbes--> - ALGERIA (Azzedine, Nadjia) Departement de Mathema...

Bayesian Nonparametric Clustering for Positive Definite Matrices.

Science.gov (United States)

Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2016-05-01

Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used. As is well-known, these algorithms need the number of clusters to be specified, which is difficult when the dataset scales. To address this issue, we resort to the classical nonparametric Bayesian framework by modeling the data as a mixture model using the Dirichlet process (DP) prior. Since these matrices do not conform to the Euclidean geometry, rather belongs to a curved Riemannian manifold,existing DP models cannot be directly applied. Thus, in this paper, we propose a novel DP mixture model framework for SPD matrices. Using the log-determinant divergence as the underlying dissimilarity measure to compare these matrices, and further using the connection between this measure and the Wishart distribution, we derive a novel DPM model based on the Wishart-Inverse-Wishart conjugate pair. We apply this model to several applications in computer vision. Our experiments demonstrate that our model is scalable to the dataset size and at the same time achieves superior accuracy compared to several state-of-the-art parametric and nonparametric clustering algorithms.

A nonparametric test for industrial specialization

OpenAIRE

Billings, Stephen B.; Johnson, Erik B.

2010-01-01

Urban economists hypothesize that industrial diversity matters for urban growth and development, but metrics for empirically testing this relationship are limited to simple concentration metrics (e.g. location quotient) or summary diversity indices (e.g. Gini, Herfindahl). As shown by recent advances in how we measure localization and specialization, these measures of industrial diversity may be subject to bias under small samples or the Modifiable Areal Unit Problem. Furthermore, empirically...

Livets febrile hemmeligheder. Et litterært slægtskab mellem Henrik Pontoppidan og Thomas Mann

DEFF Research Database (Denmark)

Vangshardt, Rasmus

filosofferne Arthur Schopenhauer og Friedrich Nietzsche – og med Thomas Mann. Det giver samtidig anledning til en revurdering af De Dødes Riges slutning: Siden bogens udgivelse har litterater diskuteret, hvorvidt dens slut-utopi er beundringsværdig eller tynd. Men Livets febrile hemmeligheder påpeger noget...

Nonparametric combinatorial sequence models.

Science.gov (United States)

Wauthier, Fabian L; Jordan, Michael I; Jojic, Nebojsa

2011-11-01

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three biological sequence families which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution over sequence representations induced by the prior. By integrating out the posterior, our method compares favorably to leading binding predictors.

Non-parametric production analysis of pesticides use in the Netherlands

NARCIS (Netherlands)

Oude Lansink, A.G.J.M.; Silva, E.

2004-01-01

Many previous empirical studies on the productivity of pesticides suggest that pesticides are under-utilized in agriculture despite the general held believe that these inputs are substantially over-utilized. This paper uses data envelopment analysis (DEA) to calculate non-parametric measures of the

Long Term Association of Tropospheric Trace gases over Pakistan by exploiting satellite observations and development of Econometric Regression based Model

Science.gov (United States)

Zeb, Naila; Fahim Khokhar, Muhammad; Khan, Saud Ahmed; Noreen, Asma; Murtaza, Rabbia

2017-04-01

Air pollution is the expected key environmental issue of Pakistan as it is ranked among top polluted countries in the region. Ongoing rapid economic growth without any adequate measures is leading to worst air quality over time. The study aims to monitor long term atmospheric composition and association of trace gases over Pakistan. Tropospheric concentrations of CO, TOC, NO2 and HCHO derived from multiple satellite instruments are used for study from year 2005 to 2014. The study will provide first database for tropospheric trace gases over Pakistan. Spatio-temporal assessment identified hotspots and possible sources of trace gases over the Pakistan. High concentrations of trace gases are mainly observed over Punjab region, which may be attributed to its metropolitan importance. It is the major agricultural, industrialized and urbanized (nearly 60 % of the Pakistan's population) sector of the country. The expected sources are the agricultural fires, biomass/fossil fuel burning for heating purposes, urbanization, industrialization and meteorological variations. Seasonal variability is observed to explore seasonal patterns over the decade. Well defined seasonal cycles of trace gases are observed over the whole study period. The observed seasonal patterns also showed some noteworthy association among trace gases, which is further explored by different statistical tests. Seasonal Mann Kendall test is applied to test the significance of trend in series whereas correlation is carried out to measure the strength of association among trace gases. Strong correlation is observed for trace gases especially between CO and TOC. Partial Mann Kendall test is used to ideally identify the impact of each covariate on long term trend of CO and TOC by partialling out each correlating trace gas (covariate). It is observed that TOC, NO2 and HCHO has significant impact on long term trend of CO whereas, TOC critically depends on NO2 concentrations for long term increase over the region

Genomic breeding value estimation using nonparametric additive regression models

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Solberg Trygve

2009-01-01

Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

Trends in Ocean Colour and Chlorophyll Concentration from 1889 to 2000, Worldwide

Science.gov (United States)

Wernand, Marcel R.; van der Woerd, Hendrik J.; Gieskes, Winfried W. C.

2013-01-01

Marine primary productivity is an important agent in the global cycling of carbon dioxide, a major ‘greenhouse gas’, and variations in the concentration of the ocean's phytoplankton biomass can therefore explain trends in the global carbon budget. Since the launch of satellite-mounted sensors globe-wide monitoring of chlorophyll, a phytoplankton biomass proxy, became feasible. Just as satellites, the Forel-Ule (FU) scale record (a hardly explored database of ocean colour) has covered all seas and oceans – but already since 1889. We provide evidence that changes of ocean surface chlorophyll can be reconstructed with confidence from this record. The EcoLight radiative transfer numerical model indicates that the FU index is closely related to chlorophyll concentrations in open ocean regions. The most complete FU record is that of the North Atlantic in terms of coverage over space and in time; this dataset has been used to test the validity of colour changes that can be translated to chlorophyll. The FU and FU-derived chlorophyll data were analysed for monotonously increasing or decreasing trends with the non-parametric Mann-Kendall test, a method to establish the presence of a consistent trend. Our analysis has not revealed a globe-wide trend of increase or decrease in chlorophyll concentration during the past century; ocean regions have apparently responded differentially to changes in meteorological, hydrological and biological conditions at the surface, including potential long-term trends related to global warming. Since 1889, chlorophyll concentrations have decreased in the Indian Ocean and in the Pacific; increased in the Atlantic Ocean, the Mediterranean, the Chinese Sea, and in the seas west and north-west of Japan. This suggests that explanations of chlorophyll changes over long periods should focus on hydrographical and biological characteristics typical of single ocean regions, not on those of ‘the’ ocean. PMID:23776435

Description and assessment of regional sea-level trends and variability from altimetry and tide gauges at the northern Australian coast

Science.gov (United States)

Gharineiat, Zahra; Deng, Xiaoli

2018-05-01

This paper aims at providing a descriptive view of the low-frequency sea-level changes around the northern Australian coastline. Twenty years of sea-level observations from multi-mission satellite altimetry and tide gauges are used to characterize sea-level trends and inter-annual variability over the study region. The results show that the interannual sea-level fingerprint in the northern Australian coastline is closely related to El Niño Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO) events, with the greatest influence on the Gulf Carpentaria, Arafura Sea, and the Timor Sea. The basin average of 14 tide-gauge time series is in strong agreement with the basin average of the altimeter data, with a root mean square difference of 18 mm and a correlation coefficient of 0.95. The rate of the sea-level trend over the altimetry period (6.3 ± 1.4 mm/yr) estimated from tide gauges is slightly higher than that (6.1 ± 1.3 mm/yr) from altimetry in the time interval 1993-2013, which can vary with the length of the time interval. Here we provide new insights into examining the significance of sea-level trends by applying the non-parametric Mann-Kendall test. This test is applied to assess if the trends are significant (upward or downward). Apart from a positive rate of sea-level trends are not statistically significant in this region due to the effects of natural variability. The findings suggest that altimetric trends are not significant along the coasts and some parts of the Gulf Carpentaria (14°S-8°S), where geophysical corrections (e.g., ocean tides) cannot be estimated accurately and altimeter measurements are contaminated by reflections from the land.

Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

DEFF Research Database (Denmark)

Høg, Esben

In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

DEFF Research Database (Denmark)

Høg, Esben

2003-01-01

In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

Science.gov (United States)

Yau, Christopher; Holmes, Chris

2011-07-01

We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

PHMB: Utilización del apósito de espuma antimicrobiana (AMD KendallTM (PHMB 0,5% en el tratamiento de las heridas crónicas

Directory of Open Access Journals (Sweden)

John Timmons

Full Text Available Abordamos la parte más problemática del tratamiento de las heridas crónicas o agudas, de acuerdo con los profesionales especializados es la infección de la herida. La sobrecarga bacteriana puede retardar la curación de la herida y disminuir la calidad del paciente como consecuencia del aumento del dolor, del exudado y del posible mal olor. Se han recopilado casos clínicos durante los últimos 6 meses en una unidad especializada en el cuidado de heridas de los hospitales Doncaster y Bassetlaw, RU. Estos casos ilustran la variedad de tipos de herida que pueden tratarse con éxito con el nuevo apósito de Espuma antimicrobiano KendallTM AMD (PHMB 0,5%. Se pudo concluir que el apósito de Espuma KendallTM AMD actúa bien como antimicrobiano y como producto de vendaje moderno. Su utilización disminuye la carga bacteriana al tiempo que consigue la absorción del exudado y el mantenimiento de un ambiente óptimo para la curación de la herida.

NONPARAMETRIC FIXED EFFECT PANEL DATA MODELS: RELATIONSHIP BETWEEN AIR POLLUTION AND INCOME FOR TURKEY

Directory of Open Access Journals (Sweden)

Rabia Ece OMAY

2013-06-01

Full Text Available In this study, relationship between gross domestic product (GDP per capita and sulfur dioxide (SO2 and particulate matter (PM10 per capita is modeled for Turkey. Nonparametric fixed effect panel data analysis is used for the modeling. The panel data covers 12 territories, in first level of Nomenclature of Territorial Units for Statistics (NUTS, for period of 1990-2001. Modeling of the relationship between GDP and SO2 and PM10 for Turkey, the non-parametric models have given good results.

Developing an immigration policy for Germany on the basis of a nonparametric labor market classification

OpenAIRE

Froelich, Markus; Puhani, Patrick

2004-01-01

Based on a nonparametrically estimated model of labor market classifications, this paper makes suggestions for immigration policy using data from western Germany in the 1990s. It is demonstrated that nonparametric regression is feasible in higher dimensions with only a few thousand observations. In sum, labor markets able to absorb immigrants are characterized by above average age and by professional occupations. On the other hand, labor markets for young workers in service occupations are id...

Characteristics of Spatial Structural Patterns and Temporal Variability of Annual Precipitation in Ningxia

Institute of Scientific and Technical Information of China (English)

无

2011-01-01

[Objective] The aim was to study the characteristics of the spatial structural patterns and temporal variability of annual precipitation in Ningxia.[Method] Using rotated empirical orthogonal function,the precipitation concentration index,wavelet analysis and Mann-Kendall rank statistic method,the characteristics of precipitation on the spatial-temporal variability and trend were analyzed by the monthly precipitation series in Ningxia during 1951-2008.[Result] In Ningxia,the spatial structural patterns of a...

The Effectiveness of Building Permit Regulation for Green Open Space at Housing Estates: Case Study of Kendal Regency, Central Java, Indonesia

Science.gov (United States)

Yulianti, Wiwik; Hadi, Sudharto P.

2018-02-01

Increasing demand for settlements steamed by population growth declines the quality of the environment specifically at urban area. The existing spatial planning could not able to prevent the change of land use for settlement and other infrastructures. The Act no. 26 of 2007 on spatial planning stipulates that green open space must reach 30% of the total area, consisting of 20% public open space and 10% private open space. The existing condition of urban area at Kendal Regency reach 245,6 million m2 with 88.145,5 m2 green open space or 0,036% out of total area. An effort to increase green open space in urban areas taken by the Government of Kendal Regency is by promulgating a local regulation stipulating that each housing developer request a building permit is obliged to provide a green open space at least 10 percent of the total housing area. This paper reviews the effectiveness of building permit regulation, the problems encountered and the concept proposed to make the local regulation work. The area of sample taken is three urban districts out of five urban districts, the resource persons chosen are those from relevant offices (Dinas) involved at the implementation of the local regulation. The data collection techniques employed are the Analytical Hierarchy Process (AHP), Geographic Information System (GIS) technology, social observation and informal interview. The data gathered will be analyzed quantitatively and qualitatively.

The Effectiveness of Building Permit Regulation for Green Open Space at Housing Estates: Case Study of Kendal Regency, Central Java, Indonesia

Directory of Open Access Journals (Sweden)

Yulianti Wiwik

2018-01-01

Full Text Available Increasing demand for settlements steamed by population growth declines the quality of the environment specifically at urban area. The existing spatial planning could not able to prevent the change of land use for settlement and other infrastructures. The Act no. 26 of 2007 on spatial planning stipulates that green open space must reach 30% of the total area, consisting of 20% public open space and 10% private open space. The existing condition of urban area at Kendal Regency reach 245,6 million m2 with 88.145,5 m2 green open space or 0,036% out of total area. An effort to increase green open space in urban areas taken by the Government of Kendal Regency is by promulgating a local regulation stipulating that each housing developer request a building permit is obliged to provide a green open space at least 10 percent of the total housing area. This paper reviews the effectiveness of building permit regulation, the problems encountered and the concept proposed to make the local regulation work. The area of sample taken is three urban districts out of five urban districts, the resource persons chosen are those from relevant offices (Dinas involved at the implementation of the local regulation. The data collection techniques employed are the Analytical Hierarchy Process (AHP, Geographic Information System (GIS technology, social observation and informal interview. The data gathered will be analyzed quantitatively and qualitatively.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications.

Directory of Open Access Journals (Sweden)

Elias Chaibub Neto

Full Text Available In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.

A comparative study of non-parametric models for identification of ...

African Journals Online (AJOL)

However, the frequency response method using random binary signals was good for unpredicted white noise characteristics and considered the best method for non-parametric system identifica-tion. The autoregressive external input (ARX) model was very useful for system identification, but on applicati-on, few input ...

On the asymptotics of the Gell-Mann-Low function in quantum field theory

International Nuclear Information System (INIS)

Kazakov, D.I.; Popov, V.S.

2003-01-01

The problem of reconstructing the Gell-Mann-Low function in quantum field theory starting with its asymptotic series with the first terms calculated by perturbation theory is discussed. And though in a strict mathematical sense this is not unambiguously realizable, under reasonable assumptions about the function it appears to be possible to reconstruct it in some finite interval of g. However, any attempts to find its asymptotics as g→∞ from our point of view are not justified. We also present the conditions under which the sum of the asymptotic series may decrease at infinity

Outlier removal, sum scores, and the inflation of the Type I error rate in independent samples t tests: the power of alternatives and recommendations.

Science.gov (United States)

Bakker, Marjan; Wicherts, Jelte M

2014-09-01

In psychology, outliers are often excluded before running an independent samples t test, and data are often nonnormal because of the use of sum scores based on tests and questionnaires. This article concerns the handling of outliers in the context of independent samples t tests applied to nonnormal sum scores. After reviewing common practice, we present results of simulations of artificial and actual psychological data, which show that the removal of outliers based on commonly used Z value thresholds severely increases the Type I error rate. We found Type I error rates of above 20% after removing outliers with a threshold value of Z = 2 in a short and difficult test. Inflations of Type I error rates are particularly severe when researchers are given the freedom to alter threshold values of Z after having seen the effects thereof on outcomes. We recommend the use of nonparametric Mann-Whitney-Wilcoxon tests or robust Yuen-Welch tests without removing outliers. These alternatives to independent samples t tests are found to have nominal Type I error rates with a minimal loss of power when no outliers are present in the data and to have nominal Type I error rates and good power when outliers are present. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

1st Conference of the International Society for Nonparametric Statistics

CERN Document Server

Lahiri, S; Politis, Dimitris

2014-01-01

This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for NonParametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI, and other organizations. M.G. Akritas, S.N. Lahiri, and D.N. Politis are the first executive committee members of ISNPS, and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao, and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world.   The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the wo...

On Parametric (and Non-Parametric Variation

Directory of Open Access Journals (Sweden)

Neil Smith

2009-11-01

Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.

Probit vs. semi-nonparametric estimation: examining the role of disability on institutional entry for older adults.

Science.gov (United States)

Sharma, Andy

2017-06-01

The purpose of this study was to showcase an advanced methodological approach to model disability and institutional entry. Both of these are important areas to investigate given the on-going aging of the United States population. By 2020, approximately 15% of the population will be 65 years and older. Many of these older adults will experience disability and require formal care. A probit analysis was employed to determine which disabilities were associated with admission into an institution (i.e. long-term care). Since this framework imposes strong distributional assumptions, misspecification leads to inconsistent estimators. To overcome such a short-coming, this analysis extended the probit framework by employing an advanced semi-nonparamertic maximum likelihood estimation utilizing Hermite polynomial expansions. Specification tests show semi-nonparametric estimation is preferred over probit. In terms of the estimates, semi-nonparametric ratios equal 42 for cognitive difficulty, 64 for independent living, and 111 for self-care disability while probit yields much smaller estimates of 19, 30, and 44, respectively. Public health professionals can use these results to better understand why certain interventions have not shown promise. Equally important, healthcare workers can use this research to evaluate which type of treatment plans may delay institutionalization and improve the quality of life for older adults. Implications for rehabilitation With on-going global aging, understanding the association between disability and institutional entry is important in devising successful rehabilitation interventions. Semi-nonparametric is preferred to probit and shows ambulatory and cognitive impairments present high risk for institutional entry (long-term care). Informal caregiving and home-based care require further examination as forms of rehabilitation/therapy for certain types of disabilities.

Global Trend Analysis of Multi-decade Soil Temperature Records Show Soils Resistant to Warming

Science.gov (United States)

Frey, S. D.; Jennings, K.

2017-12-01

Soil temperature is an important determinant of many subterranean ecological processes including plant growth, nutrient cycling, and carbon sequestration. Soils are expected to warm in response to increasing global surface temperatures; however, despite the importance of soil temperature to ecosystem processes, less attention has been given to examining changes in soil temperature over time. We collected long-term (> 20 years) soil temperature records from approximately 50 sites globally, many with multiple depths (5 - 100 cm), and examined temperature trends over the last few decades. For each site and depth we calculated annual summer means and conducted non-parametric Mann Kendall trend and Sen slope analysis to assess changes in summer soil temperature over the length of each time series. The mean summer soil temperature trend across all sites and depths was not significantly different than zero (mean = 0.004 °C year-1 ± 0.033 SD), suggesting that soils have not warmed over the observation period. Of the subset of sites that exhibit significant increases in temperature over time, site location, depth of measurement, time series length, and neither start nor end date seem to be related to trend strength. These results provide evidence that the thermal regime of soils may have a stronger buffering capacity than expected, having important implications for the global carbon cycle and feedbacks to climate change.

Nonparametric Bayesian models through probit stick-breaking processes.

Science.gov (United States)

Rodríguez, Abel; Dunson, David B

2011-03-01

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology.

Glaucoma Monitoring in a Clinical Setting Glaucoma Progression Analysis vs Nonparametric Progression Analysis in the Groningen Longitudinal Glaucoma Study

NARCIS (Netherlands)

Wesselink, Christiaan; Heeg, Govert P.; Jansonius, Nomdo M.

Objective: To compare prospectively 2 perimetric progression detection algorithms for glaucoma, the Early Manifest Glaucoma Trial algorithm (glaucoma progression analysis [GPA]) and a nonparametric algorithm applied to the mean deviation (MD) (nonparametric progression analysis [NPA]). Methods:

A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.

Science.gov (United States)

Fronczyk, Kassandra; Kottas, Athanasios

2014-03-01

We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature. © 2013, The International Biometric Society.

Kernel bandwidth estimation for non-parametric density estimation: a comparative study

CSIR Research Space (South Africa)

Van der Walt, CM

2013-12-01

Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...

A general approach to posterior contraction in nonparametric inverse problems

NARCIS (Netherlands)

Knapik, Bartek; Salomond, Jean Bernard

In this paper, we propose a general method to derive an upper bound for the contraction rate of the posterior distribution for nonparametric inverse problems. We present a general theorem that allows us to derive contraction rates for the parameter of interest from contraction rates of the related

A Powerful Test for Comparing Multiple Regression Functions.

Science.gov (United States)

Maity, Arnab

2012-09-01

In this article, we address the important problem of comparison of two or more population regression functions. Recently, Pardo-Fernández, Van Keilegom and González-Manteiga (2007) developed test statistics for simple nonparametric regression models: Y(ij) = θ(j)(Z(ij)) + σ(j)(Z(ij))∊(ij), based on empirical distributions of the errors in each population j = 1, … , J. In this paper, we propose a test for equality of the θ(j)(·) based on the concept of generalized likelihood ratio type statistics. We also generalize our test for other nonparametric regression setups, e.g, nonparametric logistic regression, where the loglikelihood for population j is any general smooth function [Formula: see text]. We describe a resampling procedure to obtain the critical values of the test. In addition, we present a simulation study to evaluate the performance of the proposed test and compare our results to those in Pardo-Fernández et al. (2007).

Performances of non-parametric statistics in sensitivity analysis and parameter ranking

International Nuclear Information System (INIS)

Saltelli, A.

1987-01-01

Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis

Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures.

Science.gov (United States)

Filippi, Sarah; Holmes, Chris C; Nieto-Barajas, Luis E

2016-11-16

In this article we propose novel Bayesian nonparametric methods using Dirichlet Process Mixture (DPM) models for detecting pairwise dependence between random variables while accounting for uncertainty in the form of the underlying distributions. A key criteria is that the procedures should scale to large data sets. In this regard we find that the formal calculation of the Bayes factor for a dependent-vs.-independent DPM joint probability measure is not feasible computationally. To address this we present Bayesian diagnostic measures for characterising evidence against a "null model" of pairwise independence. In simulation studies, as well as for a real data analysis, we show that our approach provides a useful tool for the exploratory nonparametric Bayesian analysis of large multivariate data sets.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

Science.gov (United States)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Implications of climate change on winter road networks in Ontario's Far North and northern Manitoba, Canada, based on climate model projections

Science.gov (United States)

Hori, Y.; Cheng, V. Y. S.; Gough, W. A.

2017-12-01

A network of winter roads in northern Canada connects a number of remote First Nations communities to all-season roads and rails. The extent of the winter road networks depends on the geographic features, socio-economic activities, and the numbers of remote First Nations so that it differs among the provinces. The most extensive winter road networks below the 60th parallel south are located in Ontario and Manitoba, serving 32 and 18 communities respectively. In recent years, a warmer climate has resulted in a shorter winter road season and an increase in unreliable road conditions; thus, limiting access among remote communities. This study focused on examining the future freezing degree-days (FDDs) accumulations during the winter road season at selected locations throughout Ontario's Far North and northern Manitoba using recent climate model projections from the multi-model ensembles of General Circulation Models (GCMs) under the Representative Concentration Pathway (RCP) scenarios. First, the non-parametric Mann-Kendall correlation test and the Theil-Sen method were used to identify any statistically significant trends between FDDs and time for the base period (1981-2010). Second, future climate scenarios are developed for the study areas using statistical downscaling methods. This study also examined the lowest threshold of FDDs during the winter road construction in a future period. Our previous study established the lowest threshold of 380 FDDs, which derived from the relationship between the FDDs and the opening dates of James Bay Winter Road near the Hudson-James Bay coast. Thus, this study applied the threshold measure as a conservative estimate of the minimum threshold of FDDs to examine the effects of climate change on the winter road construction period.

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

Science.gov (United States)

Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

Time series evaluation of landscape dynamics using annual Landsat imagery and spatial statistical modeling: Evidence from the Phoenix metropolitan region

Science.gov (United States)

Fan, Chao; Myint, Soe W.; Rey, Sergio J.; Li, Wenwen

2017-06-01

Urbanization is a natural and social process involving simultaneous changes to the Earth's land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective.

Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901-2010)

Science.gov (United States)

Meshram, Sarita Gajbhiye; Singh, Sudhir Kumar; Meshram, Chandrashekhar; Deo, Ravinesh C.; Ambade, Balram

2017-12-01

Trend analysis of long-term rainfall records can be used to facilitate better agriculture water management decision and climate risk studies. The main objective of this study was to identify the existing trends in the long-term rainfall time series over the period 1901-2010 utilizing 12 hydrological stations located at the Ken River basin (KRB) in Madhya Pradesh, India. To investigate the different trends, the rainfall time series data were divided into annual and seasonal (i.e., pre-monsoon, monsoon, post-monsoon, and winter season) sub-sets, and a statistical analysis of data using the non-parametric Mann-Kendall (MK) test and the Sen's slope approach was applied to identify the nature of the existing trends in rainfall series for the Ken River basin. The obtained results were further interpolated with the aid of the Quantum Geographic Information System (GIS) approach employing the inverse distance weighted approach. The results showed that the monsoon and the winter season exhibited a negative trend in rainfall changes over the period of study, and this was true for all stations, although the changes during the pre- and the post-monsoon seasons were less significant. The outcomes of this research study also suggest significant decreases in the seasonal and annual trends of rainfall amounts in the study period. These findings showing a clear signature of climate change impacts on KRB region potentially have implications in terms of climate risk management strategies to be developed during major growing and harvesting seasons and also to aid in the appropriate water resource management strategies that must be implemented in decision-making process.

Water, energy and agricultural landuse trends at Shiroro hydropower station and environs

Science.gov (United States)

Adegun, Olubunmi; Ajayi, Olalekan; Badru, Gbolahan; Odunuga, Shakirudeen

2018-02-01

The study examines the interplay among water resources, hydropower generation and agricultural landuse at the Shiroro hydropower station and its environs, in north-central Nigeria. Non-parametric trend analysis, hydropower footprint estimation, reservoir performance analysis, change detection analysis, and inferential statistics were combined to study the water-energy and food security nexus. Results of Mann-Kendall test and Sen's slope estimator for the period 1960 to 2013 showed a declining rainfall trend at Jos, around River Kaduna headwaters at -2.6 mm yr-1, while rainfall at Kaduna and Minna upstream and downstream of the reservoir respectively showed no trend. Estimates of hydropower footprint varied between 130.4 and 704.1 m3 GJ-1 between 1995 and 2013. Power generation reliability and resilience of the reservoir was 31.6 and 38.5 % respectively with year 2011 being the most vulnerable and least satisfactory. In addition to poor reliability and resilience indices, other challenges militating against good performance of hydropower generation includes population growth and climate change issues as exemplified in the downward trend observed at the headwaters. Water inflow and power generation shows a weak positive relationship with correlation coefficient (r) of 0.48, indicating less than optimal power generation. Total area of land cultivated increased from 884.59 km2 in 1986 prior to the commissioning of the hydropower station to 1730.83 km2 in 2016 which signifies an increased contribution of the dam to ensuring food security. The reality of reducing upstream rainfall amount coupled with high water footprint of electricity from the reservoir, therefore requires that a long term roadmap to improve operational coordination and management have to be put in place.

A non-parametric method for correction of global radiation observations

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Perers, Bengt

2013-01-01

in the observations are corrected. These are errors such as: tilt in the leveling of the sensor, shadowing from surrounding objects, clipping and saturation in the signal processing, and errors from dirt and wear. The method is based on a statistical non-parametric clear-sky model which is applied to both...

CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

Science.gov (United States)

Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.

Exact nonparametric inference for detection of nonlinear determinism

OpenAIRE

Luo, Xiaodong; Zhang, Jie; Small, Michael; Moroz, Irene

2005-01-01

We propose an exact nonparametric inference scheme for the detection of nonlinear determinism. The essential fact utilized in our scheme is that, for a linear stochastic process with jointly symmetric innovations, its ordinary least square (OLS) linear prediction error is symmetric about zero. Based on this viewpoint, a class of linear signed rank statistics, e.g. the Wilcoxon signed rank statistic, can be derived with the known null distributions from the prediction error. Thus one of the ad...

Spatio-temporal long-term (1950-2009) temperature trend analysis in North Carolina, United States

Science.gov (United States)

Sayemuzzaman, Mohammad; Jha, Manoj K.; Mekonnen, Ademe

2015-04-01

This study analyzed long-term (1950-2009) annual and seasonal time series data of maximum and minimum temperature from 249 uniformly distributed stations across the State of North Carolina, United States. The Mann-Kendall and Theil-Sen approach were applied to quantify the significance and magnitude of trend, respectively. A pre-whitening technique was applied to eliminate the effect of lag-1 serial correlation. For most stations over the period of the past 60 years, the difference between minimum and maximum temperatures was found decreasing with an overall increasing trend in the mean temperature. However, significant trends (confidence level ≥ 95 %) in the mean temperature analysis were detected only in 20, 3, 23, and 20 % of the stations in summer, winter, autumn, and spring, respectively. The magnitude of the highest warming trend in minimum temperature and the highest cooling trend in maximum temperature was +0.073 °C/year in the autumn season and -0.12 °C/year in the summer season, respectively. Additional analysis in mean temperature trend was conducted on three regions of North Carolina (mountain, piedmont, and coastal). The results revealed a warming trend for the coastal zone, a cooling trend for the mountain zone, and no distinct trend for the piedmont zone. The Sequential Mann-Kendall test results indicated that the significant increasing trends in minimum temperature and decreasing trend in maximum temperature had begun around 1970 and 1960 (change point), respectively, in most of the stations. Finally, the comparison between mean surface air temperature (SAT) and the North Atlantic Oscillation (NAO) concluded that the variability and trend in SAT can be explained partially by the NAO index for North Carolina.

Performance of non-parametric algorithms for spatial mapping of tropical forest structure

Directory of Open Access Journals (Sweden)

Liang Xu

2016-08-01

Full Text Available Abstract Background Mapping tropical forest structure is a critical requirement for accurate estimation of emissions and removals from land use activities. With the availability of a wide range of remote sensing imagery of vegetation characteristics from space, development of finer resolution and more accurate maps has advanced in recent years. However, the mapping accuracy relies heavily on the quality of input layers, the algorithm chosen, and the size and quality of inventory samples for calibration and validation. Results By using airborne lidar data as the “truth” and focusing on the mean canopy height (MCH as a key structural parameter, we test two commonly-used non-parametric techniques of maximum entropy (ME and random forest (RF for developing maps over a study site in Central Gabon. Results of mapping show that both approaches have improved accuracy with more input layers in mapping canopy height at 100 m (1-ha pixels. The bias-corrected spatial models further improve estimates for small and large trees across the tails of height distributions with a trade-off in increasing overall mean squared error that can be readily compensated by increasing the sample size. Conclusions A significant improvement in tropical forest mapping can be achieved by weighting the number of inventory samples against the choice of image layers and the non-parametric algorithms. Without future satellite observations with better sensitivity to forest biomass, the maps based on existing data will remain slightly biased towards the mean of the distribution and under and over estimating the upper and lower tails of the distribution.

Promotion time cure rate model with nonparametric form of covariate effects.

Science.gov (United States)

Chen, Tianlei; Du, Pang

2018-05-10

Survival data with a cured portion are commonly seen in clinical trials. Motivated from a biological interpretation of cancer metastasis, promotion time cure model is a popular alternative to the mixture cure rate model for analyzing such data. The existing promotion cure models all assume a restrictive parametric form of covariate effects, which can be incorrectly specified especially at the exploratory stage. In this paper, we propose a nonparametric approach to modeling the covariate effects under the framework of promotion time cure model. The covariate effect function is estimated by smoothing splines via the optimization of a penalized profile likelihood. Point-wise interval estimates are also derived from the Bayesian interpretation of the penalized profile likelihood. Asymptotic convergence rates are established for the proposed estimates. Simulations show excellent performance of the proposed nonparametric method, which is then applied to a melanoma study. Copyright © 2018 John Wiley & Sons, Ltd.

Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

Science.gov (United States)

Kumar, Sricharan; Srivistava, Ashok N.

2012-01-01

Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems.

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks

Science.gov (United States)

Gray-Davies, Tristan; Holmes, Chris C.; Caron, François

2018-01-01

We present a novel Bayesian nonparametric regression model for covariates X and continuous response variable Y ∈ ℝ. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the stochastic ordering of the conditional distributions F (y|x). By adopting an approximate composite likelihood approach, we show that the resulting posterior inference can be decoupled for the separate components of the model. This procedure can scale to very large datasets and allows for the use of standard, existing, software from Bayesian nonparametric density estimation and Plackett-Luce ranking estimation to be applied. As an illustration, we show an application of our approach to a US Census dataset, with over 1,300,000 data points and more than 100 covariates. PMID:29623150

A method of statistical analysis in the field of sports science when assumptions of parametric tests are not violated

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Elżbieta Sandurska

2016-12-01

Full Text Available Introduction: Application of statistical software typically does not require extensive statistical knowledge, allowing to easily perform even complex analyses. Consequently, test selection criteria and important assumptions may be easily overlooked or given insufficient consideration. In such cases, the results may likely lead to wrong conclusions. Aim: To discuss issues related to assumption violations in the case of Student's t-test and one-way ANOVA, two parametric tests frequently used in the field of sports science, and to recommend solutions. Description of the state of knowledge: Student's t-test and ANOVA are parametric tests, and therefore some of the assumptions that need to be satisfied include normal distribution of the data and homogeneity of variances in groups. If the assumptions are violated, the original design of the test is impaired, and the test may then be compromised giving spurious results. A simple method to normalize the data and to stabilize the variance is to use transformations. If such approach fails, a good alternative to consider is a nonparametric test, such as Mann-Whitney, the Kruskal-Wallis or Wilcoxon signed-rank tests. Summary: Thorough verification of the parametric tests assumptions allows for correct selection of statistical tools, which is the basis of well-grounded statistical analysis. With a few simple rules, testing patterns in the data characteristic for the study of sports science comes down to a straightforward procedure.

A diagnosis of modern life: Robert Musil’s Der Mann ohne Eigenschaften as a critical-utopian project

NARCIS (Netherlands)

de Cauwer, S.

2012-01-01

Robert Musil wrote Der Mann ohne Eigenschaften as a critical intervention in the intellectual debates of his time. There are three general questions which prevail in the Musil scholarship: 1. What exactly did he want to critique and how is this critique at work in the novel? 2. What were his aims

A structural nonparametric reappraisal of the CO2 emissions-income relationship

NARCIS (Netherlands)

Azomahou, T.T.; Goedhuys - Degelin, Micheline; Nguyen-Van, P.

Relying on a structural nonparametric estimation, we show that co2 emissions clearly increase with income at low income levels. For higher income levels, we observe a decreasing relationship, though not significant. We also find thatco2 emissions monotonically increases with energy use at a

Nonparametric estimation of the stationary M/G/1 workload distribution function

DEFF Research Database (Denmark)

Hansen, Martin Bøgsted

2005-01-01

In this paper it is demonstrated how a nonparametric estimator of the stationary workload distribution function of the M/G/1-queue can be obtained by systematic sampling the workload process. Weak convergence results and bootstrap methods for empirical distribution functions for stationary associ...

Impulse response identification with deterministic inputs using non-parametric methods

International Nuclear Information System (INIS)

Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

1985-01-01

This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

Nonparametric Estimation of Interval Reliability for Discrete-Time Semi-Markov Systems

DEFF Research Database (Denmark)

Georgiadis, Stylianos; Limnios, Nikolaos

2016-01-01

In this article, we consider a repairable discrete-time semi-Markov system with finite state space. The measure of the interval reliability is given as the probability of the system being operational over a given finite-length time interval. A nonparametric estimator is proposed for the interval...

Assessing pupil and school performance by non-parametric and parametric techniques

NARCIS (Netherlands)

de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.

2010-01-01

This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall

Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

NARCIS (Netherlands)

Yoo, W.W.; Ghosal, S

2016-01-01

In the setting of nonparametric multivariate regression with unknown error variance, we study asymptotic properties of a Bayesian method for estimating a regression function f and its mixed partial derivatives. We use a random series of tensor product of B-splines with normal basis coefficients as a

A non-parametric hierarchical model to discover behavior dynamics from tracks

NARCIS (Netherlands)

Kooij, J.F.P.; Englebienne, G.; Gavrila, D.M.

2012-01-01

We present a novel non-parametric Bayesian model to jointly discover the dynamics of low-level actions and high-level behaviors of tracked people in open environments. Our model represents behaviors as Markov chains of actions which capture high-level temporal dynamics. Actions may be shared by

Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables

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Sandvik Leiv

2011-04-01

Full Text Available Abstract Background The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables. Methods Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure. Results The Welch U test (the T test with adjustment for unequal variances and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group. The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily. Conclusions The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.

La place du roman Der Untertan au sein de l'œuvre d'Heinrich Mann

OpenAIRE

Teinturier , Frédéric

2009-01-01

Der Untertan is one of the central works in H. Mann's production : this novel is an achievement and reveals the author's esthetical and political evolution. Furthermore, this novel shows an original conception of literature, because the words of the characters are completed and qualified by the ones the novelist expresses in his essays. Besides, Der Untertan can be regarded as the counterpart of Die kleine Stadt: only the confrontation of both novels makes it possible to understand the author...

Using non-parametric methods in econometric production analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...

Estimation of Stochastic Volatility Models by Nonparametric Filtering

DEFF Research Database (Denmark)

Kanaya, Shin; Kristensen, Dennis

2016-01-01

/estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases...... and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties...

Nonparametric Bayesian inference in biostatistics

CERN Document Server

Müller, Peter

2015-01-01

As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...

Hadron Energy Reconstruction for ATLAS Barrel Combined Calorimeter Using Non-Parametrical Method

CERN Document Server

Kulchitskii, Yu A

2000-01-01

Hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter in the framework of the non-parametrical method is discussed. The non-parametrical method utilizes only the known e/h ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to fast energy reconstruction in a first level trigger. The reconstructed mean values of the hadron energies are within \\pm1% of the true values and the fractional energy resolution is [(58\\pm 3)%{\\sqrt{GeV}}/\\sqrt{E}+(2.5\\pm0.3)%]\\bigoplus(1.7\\pm0.2) GeV/E. The value of the e/h ratio obtained for the electromagnetic compartment of the combined calorimeter is 1.74\\pm0.04. Results of a study of the longitudinal hadronic shower development are also presented.

Sport Tourism Centres from Top Athletes’ Perspective: Differences among Sport Groups

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Polanec Anze

2014-09-01

Full Text Available Background: Sport tourism plays an important role in the tourism industry and consequently in the economy. Sport tourism centres as providers of sport services need to be familiar with the basic needs of their customers and tailor their services accordingly. Objectives: The aim of the paper is to determine the models for customizing sport tourism services to address the needs specific for an individual sport. Methods/Approach: A questionnaire has been created and sent electronically or physically to top athletes from Slovenia, Central and Eastern Europe. Respondents were mainly from Slovenia and mostly representatives of national sports federations. The Mann Whitney and the Kruskall-Wallis tests were applied in order to test differences among sport groups. Results: The conducted Mann-Whitney non-parametric tests show that representatives of different sport groups have different perspectives on sport tourism services. Conclusions: The results of the study can be used by sport tourism centres in the process of tailoring their services, planning marketing activities or developing strategic projects.

Bayesian nonparametric estimation of continuous monotone functions with applications to dose-response analysis.

Science.gov (United States)

Bornkamp, Björn; Ickstadt, Katja

2009-03-01

In this article, we consider monotone nonparametric regression in a Bayesian framework. The monotone function is modeled as a mixture of shifted and scaled parametric probability distribution functions, and a general random probability measure is assumed as the prior for the mixing distribution. We investigate the choice of the underlying parametric distribution function and find that the two-sided power distribution function is well suited both from a computational and mathematical point of view. The model is motivated by traditional nonlinear models for dose-response analysis, and provides possibilities to elicitate informative prior distributions on different aspects of the curve. The method is compared with other recent approaches to monotone nonparametric regression in a simulation study and is illustrated on a data set from dose-response analysis.

Low default credit scoring using two-class non-parametric kernel density estimation

CSIR Research Space (South Africa)

Rademeyer, E

2016-12-01

Full Text Available This paper investigates the performance of two-class classification credit scoring data sets with low default ratios. The standard two-class parametric Gaussian and non-parametric Parzen classifiers are extended, using Bayes’ rule, to include either...

Profile of Students' Creative Thinking Skills on Quantitative Project-Based Protein Testing using Local Materials

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D. K. Sari

2017-04-01

Full Text Available The purpose of this study is to obtain a profile of students’ creative thinking skills on quantitative project-based protein testing using local materials. Implementation of the research is using quasi-experimental method pre-test post-test control group design with 40 students involved in Biochemistry lab. The research instrument is pre-test and post-test using creative thinking skills in the form of description and students’ questionnaire. The analysis was performed with SPSS 22.0 program to see the significance normality, U Mann-Whitney test for nonparametric statistics, N-Gain score, and the percentage of student responses to the practicum performed. The research result shows that the pretest rate in the experimental group is 8.25 while in the control group is 6.90. After attending a project-based practicum with local materials, the experimental group obtained the mean of posttest is 37.55 while in control class is 11.18. The students’ improvement on creative thinking skills can be seen from the average of N-Gain in the experimental class with 0.32 (medium category and in the control category with 0.05 (low category. The experimental and control class have different creative thinking skills significantly different fluency, flexibility, novelty, and detail. It can be concluded that quantitative project-based protein testing using local materials can improve students’ creative thinking skills. 71% of total students feel that quantitative project-based protein testing using local materials make them more creative in doing a practicum in the laboratory.

Comparison of parametric and bootstrap method in bioequivalence test.

Science.gov (United States)

Ahn, Byung-Jin; Yim, Dong-Seok

2009-10-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

20th century trends of drought conditions in the Mediterranean: the influence of large-scale circulation patterns.

Science.gov (United States)

Sousa, Pedro; Trigo, Ricardo; Garcia-Herrera, Ricardo

2010-05-01

Here we have used the Self Calibrated PDSI (scPDSI) proposed by Wells et al (2004) as a more appropriate approach to characterize drought conditions in the Mediterranean area. The scPDSI has been shown to perform better (than the original PDSI) when evaluating spatial and temporal drought characteristics for regions outside the USA (Schrier et al, 2005). Seasonal and annual trends for the 1901-2000, 1901-1950 and 1951-2000 periods were computed using the standard Mann-Kendall test for trend significance evaluation. However, statistical significance obtained with this test can be highly misleading because it does not take into account the low variability nature that dominates the seasonal evolution of scPDSI fields. We have now improved these results by employing a modified Mann-Kendall test for auto-correlated series (Hamed and Ramachandra, 1997), such as the scPDSI case. This development allowed for a better definition of the Mediterranean areas characterized by significant changes in the scPDSI, namely the largely negative trends that dominate the Mediterranean basin, with the exceptions of parts of eastern Turkey and northwestern Iberia, since initially these areas were overestimated. The spatio-temporal variability of these indices was evaluated with an EOF analysis, in order to reduce the large dimensionality of the fields under analysis. Spatial representation of the first EOF patterns shows that EOF 1 covers the entire Mediterranean basin (16.4% of EV), while EOF2 is dominated by a W-E dipole (10% EV). The following EOF patterns present smaller scale features, and explain smaller amounts of variance. The EOF patterns have also facilitated the definition of four sub-regions with large socio-economic relevance: 1) Iberia, 2) Italian Peninsula, 3) Balkans and 4) Turkey. Afterwards we perform a comprehensive analysis on the links between the scPDSI and the large-scale atmospheric circulation indices that affect the Mediterranean basin, namely; NAO, EA, and SCAND

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

Science.gov (United States)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a

Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

DEFF Research Database (Denmark)

Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

Psychosocial risk factors in medical personnel of a health service in Cartagena de Indias, Colombia

Directory of Open Access Journals (Sweden)

Irma Y. Castillo Á

2011-11-01

Full Text Available Objective: to determine the variables associated with psychosocial risk factors among the doctors of a stateowned social welfare enterprise providing health services in Cartagena. Methodology: a cross-sectional study on a population of 197 doctors from the enterprise’s outpatient and emergency services. The istas21 questionnaire, a Spanish adaptation of the Copenhagen Psychosocial Questionnaire (copsoq, was used to assess psychosocial factors. Statistical analysis was performed using the program SPSS® version 17, and the non-parametric Mann-Whitney U test was applied to estimate the associations between variables. Results: 170 doctors participated in this study; 88.8% of which had favorable exposure to risk factors in the following dimensions: social support and quality of leadership and Double presence. 69.4% showed adverse exposure in the insecurity dimension. In the dimensions Insecurity and Double Presence, general practitioners were in worse conditions than specialists (Mann-Whitney U Prob<0.05. Additionally, doctors from the outpatient service showed more deterioration in the social support and quality of leadership dimensions than those from the emergency service (Mann-Whitney U Prob<0.05. As for the psychological demands dimension, doctors from higher socioeconomic strata showed higher unfavorable scores than those from lower strata (Mann-Whitney U Prob<0.05.

Initial Efficacy Testing of an Autobiographical Memory Intervention on Advance Care Planning for Patients With Terminal Cancer.

Science.gov (United States)

Brohard, Cheryl

2017-11-01

To test the efficacy of a novel intervention to facilitate advance care planning.
. Exploratory, quasiexperimental pilot study with two independent groups.
. A large hospice located in the southwestern United States. 
. A convenience sample of 50 participants with terminal cancer enrolled in hospice.
. An autobiographical memory (ABM) intervention used the participants' experiences with cancer and end of life for the purpose of directing advance care planning.
. Two domains of advance care planning, decision making and communication, were measured in relation to 11 variables. The ABM intervention was nonthreatening, short in duration, and easily completed with participants as they recalled, without hesitation, specific personal memories of family and friends who had died and their advance care plans. The Mann-Whitney nonparametric test revealed that participants in the experimental group had a higher average rank than those in the control group for communicating the decision about antibiotics, as well as exhibited a trend toward significance for five other advance care planning variables.
. Findings showed that directive ABMs may be effective in influencing the decision making and communication of advance care planning for terminally ill patients with cancer.
. The current level of understanding about using the ABM intervention suggests that nurses can initiate an advance care planning conversation using this approach.

The gap between knowledge on HIV/AIDS and sexual behavior: a study of teenagers in Vespasiano, Minas Gerais State, Brazil La laguna entre el conocimiento sobre VIH/SIDA y el comportamiento sexual: una investigación con adolescentes de Vespasiano, Minas Gerais, Brasil A lacuna entre o conhecimento sobre HIV/AIDS e o comportamento sexual: uma investigação com adolescentes de Vespasiano, Minas Gerais, Brasil

Directory of Open Access Journals (Sweden)

Eugênio Marcos de Andrade Goulart

2013-05-01

Full Text Available The aim of this study was to investigate gaps between knowledge on HIV/AIDS and sexual behavior among teenagers. The study used a cross-sectional design with a representative random sample of 1,158 teenagers (14 to 19 years of age enrolled in nine public secondary schools and who answered validated questionnaires. Data analysis included descriptive statistics and tests of hypotheses (chi-square, Mann-Whitney and Kruskal-Wallis, Kendall, and Fisher's exact test. The vast majority of the teenagers (98.7% expressed doubt on at least one question. Condom use during first sexual intercourse was significantly associated with condom use in sexual relations in the previous six months. There was no statistical association between knowledge on HIV/AIDS and frequency of condom use or number of sexual partners. Health actions are needed that link schools to health services, in addition to not only elaborating appropriate information but also valorizing teenagers' individuality in the development of proposalsEl objetivo fue investigar las lagunas entre el conocimiento sobre el VIH/SIDA y el comportamiento sexual en adolescentes de enseñanza media. Delineación transversal con muestra representativa y aleatoria de 1.158 adolescentes entre 14 a 19 años, matriculados en nueve escuelas públicas que respondieron a cuestionarios validados. El análisis de los datos implicó estadística descriptiva y tests de hipótesis (chi-cuadrado, Mann-Whitney y Kruskal-Wallis, Kendal y test exacto de Fisher. La mayoría de los adolescentes (98,7% presentó dudas en alguna cuestión propuesta. El uso del preservativo en la primera relación sexual influenció el uso en las relaciones de los últimos seis meses. No hubo asociación estadística entre el conocimiento sobre VIH/SIDA con la frecuencia del uso de preservativo y la multiplicidad de compañeros sexuales. Es necesaria la implementación de acciones en salud que articulen la escuela a los servicios de salud y que

Microcosmos the world of elementary particles : fictional discussions between Einstein, Newton, and Gell-Mann

CERN Document Server

Fritzsch, Harald

2014-01-01

This book provides a broad introduction into the field of particle physics for the general reader through virtual discussions among prominent physicists, Albert Einstein, Murray Gell-Mann, Issac Newton and a modern physicists. Matter is composed of quarks and electrons. The electrons interact with the atomic nuclei by the exchange of photons. The forces between the quarks are generated by the exchange of gluons, which leads to the confinement of the quarks. The weak bosons provide the weak forces among the leptons and quarks. The book is suitable for non-experts in physics. Readership: General readers, students and researchers in physics.

EX-DIVIDEND DATE DAN PERUBAHAN HARGA SAHAM

Directory of Open Access Journals (Sweden)

Novriyanthi Taungke

2015-12-01

Full Text Available The aim of this study is to analyze whether the stock prices decrease at ex-dividend date in Indonesia Stock Exchange (IDX that is determined by amount of dividend drop-off ratio (DDR. This study also attempts to investigate the differences the stock prices decrease at ex-dividend date based on Investment Opportunity Set (IOS. Sample consist of  the companiesthat announced the dividend during 2010-2012 periods. By using non-parametric tests, especially Chi-square Test and Mann Whitney Test,  the result of this study showed the stock prices decreased less than dividend amount on ex-dividend date. Besides, the non-growth firms experienced decrease more than growth firms.

A multi-instrument non-parametric reconstruction of the electron pressure profile in the galaxy cluster CLJ1226.9+3332

Science.gov (United States)

Romero, C.; McWilliam, M.; Macías-Pérez, J.-F.; Adam, R.; Ade, P.; André, P.; Aussel, H.; Beelen, A.; Benoît, A.; Bideaud, A.; Billot, N.; Bourrion, O.; Calvo, M.; Catalano, A.; Coiffard, G.; Comis, B.; de Petris, M.; Désert, F.-X.; Doyle, S.; Goupy, J.; Kramer, C.; Lagache, G.; Leclercq, S.; Lestrade, J.-F.; Mauskopf, P.; Mayet, F.; Monfardini, A.; Pascale, E.; Perotto, L.; Pisano, G.; Ponthieu, N.; Revéret, V.; Ritacco, A.; Roussel, H.; Ruppin, F.; Schuster, K.; Sievers, A.; Triqueneaux, S.; Tucker, C.; Zylka, R.

2018-04-01

Context. In the past decade, sensitive, resolved Sunyaev-Zel'dovich (SZ) studies of galaxy clusters have become common. Whereas many previous SZ studies have parameterized the pressure profiles of galaxy clusters, non-parametric reconstructions will provide insights into the thermodynamic state of the intracluster medium. Aim. We seek to recover the non-parametric pressure profiles of the high redshift (z = 0.89) galaxy cluster CLJ 1226.9+3332 as inferred from SZ data from the MUSTANG, NIKA, Bolocam, and Planck instruments, which all probe different angular scales. Methods: Our non-parametric algorithm makes use of logarithmic interpolation, which under the assumption of ellipsoidal symmetry is analytically integrable. For MUSTANG, NIKA, and Bolocam we derive a non-parametric pressure profile independently and find good agreement among the instruments. In particular, we find that the non-parametric profiles are consistent with a fitted generalized Navaro-Frenk-White (gNFW) profile. Given the ability of Planck to constrain the total signal, we include a prior on the integrated Compton Y parameter as determined by Planck. Results: For a given instrument, constraints on the pressure profile diminish rapidly beyond the field of view. The overlap in spatial scales probed by these four datasets is therefore critical in checking for consistency between instruments. By using multiple instruments, our analysis of CLJ 1226.9+3332 covers a large radial range, from the central regions to the cluster outskirts: 0.05 R500 generation of SZ instruments such as NIKA2 and MUSTANG2.

Analyzing cost efficient production behavior under economies of scope : A nonparametric methodology

NARCIS (Netherlands)

Cherchye, L.J.H.; de Rock, B.; Vermeulen, F.M.P.

2008-01-01

In designing a production model for firms that generate multiple outputs, we take as a starting point that such multioutput production refers to economies of scope, which in turn originate from joint input use and input externalities. We provide a nonparametric characterization of cost-efficient

A non-parametric Bayesian approach to decompounding from high frequency data

NARCIS (Netherlands)

Gugushvili, Shota; van der Meulen, F.H.; Spreij, Peter

2016-01-01

Given a sample from a discretely observed compound Poisson process, we consider non-parametric estimation of the density f0 of its jump sizes, as well as of its intensity λ0. We take a Bayesian approach to the problem and specify the prior on f0 as the Dirichlet location mixture of normal densities.

Semi-Nonparametric Estimation and Misspecification Testing of Diffusion Models

DEFF Research Database (Denmark)

Kristensen, Dennis

of the estimators and tests under the null are derived, and the power properties are analyzed by considering contiguous alternatives. Test directly comparing the drift and diffusion estimators under the relevant null and alternative are also analyzed. Markov Bootstrap versions of the test statistics are proposed...... to improve on the finite-sample approximations. The finite sample properties of the estimators are examined in a simulation study....

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

Science.gov (United States)

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Observed climatic changes in Shanghai during 1873-2002%上海市100余年来气候变化(1873-2002)

Institute of Scientific and Technical Information of China (English)

张强; 陈家其; 张增信

2005-01-01

Variation characteristics of temperature and precipitation in January and July and annual mean temperature and annual precipitation are analyzed with the help of cumulative anomalies, Mann-Kendall analysis and wavelet analysis. The research results indicate that January precipitation presents an increasing trend after 1990, wavelet analysis result suggests that this increasing trend will continue in the near future. The changes of July precipitation present different features. During 1900-1960, July precipitation is in a rising trend, but is in a declining trend after 1960. Wavelet analysis shows that this declining trend will go on in the near future. Temperature variations in Shanghai are in fluctuations with 2 to 3 temperature rising periods. Mann-Kendall analysis indicates that temperature variations have the obvious abrupt change time when compared with precipitation changes in Shanghai during the past 100 years. The abrupt change time of January temperature lies in 1985, and that of July temperature lies in 1931-1933 and annual mean temperature has the abrupt change time in 1923-1930. Except July precipitation, the precipitation in January, temperature in January, July and annual mean temperature, and annual precipitation are also in a rising trend in the near future. The research results in this paper may be meaningful for future further climatic changes of Shanghai and social mitigation of climatic disasters in the future.

Observed climatic changes in Shanghai during 1873-2002

Institute of Scientific and Technical Information of China (English)

ZHANGQiang; CHENJiaqi; ZHANGZengxin

2005-01-01

Variation characteristics of temperature and precipitation in January and July and annual mean temperature and annual precipitation are analyzed with the help of cumulative anomalies,Mann-Kendall analysis and wavelet analysis. The research results indicate that January precipitation presents an increasing trend after 1990, wavelet analysis result suggests that this increasing trend will continue in the near future. The changes of July precipitation present different features. During 1900-1960, July precipitation is in a rising trend, but is in a declining trend after 1960. Wavelet analysis shows that this declining trend will go on in the near future. Temperature variations in Shanghai are in fluctuations with 2 to 3 temperature rising periods. Mann-Kendall analysis indicates that temperature variations have the obvious abrupt change time when compared with precipitation changes in Shanghai during the past 100 years. The abrupt change time of January temperature lies in 1985, and that of July temperature lies in 1931-1933 and annual mean temperature has the abrupt change time in 1923-1930. Except July precipitation, the precipitation in January, temperature in January, July and annual mean temperature, and annual precipitation are also in a rising trend in the near future. The research results in this paper may be meaningful for future further climatic changes of Shanghai and social mitigation of climatic disasters in the future.

Non-parametric Bayesian graph models reveal community structure in resting state fMRI

DEFF Research Database (Denmark)

Andersen, Kasper Winther; Madsen, Kristoffer H.; Siebner, Hartwig Roman

2014-01-01

Modeling of resting state functional magnetic resonance imaging (rs-fMRI) data using network models is of increasing interest. It is often desirable to group nodes into clusters to interpret the communication patterns between nodes. In this study we consider three different nonparametric Bayesian...... models for node clustering in complex networks. In particular, we test their ability to predict unseen data and their ability to reproduce clustering across datasets. The three generative models considered are the Infinite Relational Model (IRM), Bayesian Community Detection (BCD), and the Infinite...... between clusters. BCD restricts the between-cluster link probabilities to be strictly lower than within-cluster link probabilities to conform to the community structure typically seen in social networks. IDM only models a single between-cluster link probability, which can be interpreted as a background...

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Science.gov (United States)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Directory of Open Access Journals (Sweden)

Jinchao Feng

2018-03-01

Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Efficient nonparametric n -body force fields from machine learning

Science.gov (United States)

Glielmo, Aldo; Zeni, Claudio; De Vita, Alessandro

2018-05-01

We provide a definition and explicit expressions for n -body Gaussian process (GP) kernels, which can learn any interatomic interaction occurring in a physical system, up to n -body contributions, for any value of n . The series is complete, as it can be shown that the "universal approximator" squared exponential kernel can be written as a sum of n -body kernels. These recipes enable the choice of optimally efficient force models for each target system, as confirmed by extensive testing on various materials. We furthermore describe how the n -body kernels can be "mapped" on equivalent representations that provide database-size-independent predictions and are thus crucially more efficient. We explicitly carry out this mapping procedure for the first nontrivial (three-body) kernel of the series, and we show that this reproduces the GP-predicted forces with meV /Å accuracy while being orders of magnitude faster. These results pave the way to using novel force models (here named "M-FFs") that are computationally as fast as their corresponding standard parametrized n -body force fields, while retaining the nonparametric character, the ease of training and validation, and the accuracy of the best recently proposed machine-learning potentials.

Discrete non-parametric kernel estimation for global sensitivity analysis

International Nuclear Information System (INIS)

Senga Kiessé, Tristan; Ventura, Anne

2016-01-01

This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

Analyzing Cost Efficient Production Behavior Under Economies of Scope : A Nonparametric Methodology

NARCIS (Netherlands)

Cherchye, L.J.H.; de Rock, B.; Vermeulen, F.M.P.

2006-01-01

In designing a production model for firms that generate multiple outputs, we take as a starting point that such multi-output production refers to economies of scope, which in turn originate from joint input use and input externalities. We provide a nonparametric characterization of cost efficient

Digital spectral analysis parametric, non-parametric and advanced methods

CERN Document Server

Castanié, Francis

2013-01-01

Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

KAUST Repository

Dai, Wenlin; Tong, Tiejun; Zhu, Lixing

2017-01-01

Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

KAUST Repository

Dai, Wenlin

2017-09-01

Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

Nonparametric Second-Order Theory of Error Propagation on Motion Groups.

Science.gov (United States)

Wang, Yunfeng; Chirikjian, Gregory S

2008-01-01

Error propagation on the Euclidean motion group arises in a number of areas such as in dead reckoning errors in mobile robot navigation and joint errors that accumulate from the base to the distal end of kinematic chains such as manipulators and biological macromolecules. We address error propagation in rigid-body poses in a coordinate-free way. In this paper we show how errors propagated by convolution on the Euclidean motion group, SE(3), can be approximated to second order using the theory of Lie algebras and Lie groups. We then show how errors that are small (but not so small that linearization is valid) can be propagated by a recursive formula derived here. This formula takes into account errors to second-order, whereas prior efforts only considered the first-order case. Our formulation is nonparametric in the sense that it will work for probability density functions of any form (not only Gaussians). Numerical tests demonstrate the accuracy of this second-order theory in the context of a manipulator arm and a flexible needle with bevel tip.

Goodness-of-fit tests in mixed models

KAUST Repository

Claeskens, Gerda

2009-05-12

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest. Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution. © 2009 Sociedad de Estadística e Investigación Operativa.

Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors

Directory of Open Access Journals (Sweden)

Xibin Zhang

2016-04-01

Full Text Available This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density. The error density is approximated by the kernel density estimator of the unobserved errors, while the regression function is estimated using the Nadaraya-Watson estimator admitting continuous and discrete regressors. We derive an approximate likelihood and posterior for bandwidth parameters, followed by a sampling algorithm. Simulation results show that the proposed approach typically leads to better accuracy of the resulting estimates than cross-validation, particularly for smaller sample sizes. This bandwidth estimation approach is applied to nonparametric regression model of the Australian All Ordinaries returns and the kernel density estimation of gross domestic product (GDP growth rates among the organisation for economic co-operation and development (OECD and non-OECD countries.

Estimation of the limit of detection with a bootstrap-derived standard error by a partly non-parametric approach. Application to HPLC drug assays

DEFF Research Database (Denmark)

Linnet, Kristian

2005-01-01

Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...

Understanding of social capital condition among red guava farmers in Tambahrejo Village, Pageruyung District, Kendal Regency

Science.gov (United States)

Gayatri, S.; Sumarjono, D.; Satmoko, S.

2018-01-01

The aim of the study was to explore the potential of social capital and growing income of red guava farmers in Tambahrejo Village, Pageruyung District, Kendal Regency. Interview and observation were used for data collection. Set of Questionnaire was developed to answer research’ goal. All member of farmer group I ACC (Kelompok Tani Makmur I ACC) were chosen as respondents in this research. Data were analyzed using multiple regressions. The result shows that there was significant relationship between social capital in community and the income of the red guava farmers. Farmer’ group was found as a media to improve farmers’ knowledge and networking. Farmers group facilitated farmers to market red guava product. Moreover, wife of the farmers established women group or KWT (Kelompok Wanita Tani). The result found that KWT contributed to improve family’s income. KWT also promote activities to help product’s diversification of red guava. Both farmer group and KWT provided activities such as saving and loans, it means there was trust among member of farmer group.

PEDAGANG WARUNG KELI: Studi Eko-Sosial Religius Wanita Pedagang Tradisional Di Desa Jambearum Kendal Jawa Tengah

Directory of Open Access Journals (Sweden)

Lutfiyah Lutfiah

2017-02-01

Full Text Available Women in a family have a role as a spouse, a sweetheart or a mother. Women have a right to determine and concrete a happiness either immaterial or material. In Jambearum, Kendal, Central Java, there were some women who played a role of helping her husband, by becoming a vendor, or known as warung keli. The role woman as a wife and the role for helping husband did not make them to stop becoming a religious-social being as well. This research is a qualitative descriptive which used social anthropology approach. This research aimed to determine: 1Women who have extra job to earn a living, are tough. 2 The time management is, these women began to accomplish domestic activities after fajr until 08.00 AM, then they started to kulaan in village market before selling around. Religius social activities were conducted as best as they can, some of them were active, others were moderate and less active. 3 The contributions given by these women can not be mentioned significantly.

A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

Directory of Open Access Journals (Sweden)

Archer Kellie J

2008-02-01

Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

Responses of streamflow and sediment load to climate change and human activity in the Upper Yellow River, China: a case of the Ten Great Gullies Basin.

Science.gov (United States)

Liu, Tong; Huang, He Qing; Shao, Mingan; Yao, Wenyi; Gu, Jing; Yu, Guoan

2015-01-01

Soil erosion and land desertification are the most serious environmental problems globally. This study investigated the changes in streamflow and sediment load from 1964 to 2012 in the Ten Great Gullies area of the Upper Yellow River. Tests for gradual trends (Mann-Kendall test) and abrupt changes (Pettitt test) identify that significant declines in streamflow and sediment load occurred in 1997-1998 in two typical gullies. A comparison of climatic variability before and after the change points shows no statistically significant trends in annual precipitation and potential evapotranspiration. Human activities have been very active in the region and during 1990-2010, 146.01 and 197.62 km2 of land were converted, respectively, to forests and grassland, with corresponding increases of 87.56 and 77.05%. In addition, a large number of check dams have been built up in the upper reaches of the ten gullies. These measures were likely responsible for the significant decline in the annual streamflow and sediment load over the last 49 years.

Assessing natural and anthropogenic influences on water discharge and sediment load in the Yangtze River, China.

Science.gov (United States)

Zhao, Yifei; Zou, Xinqing; Liu, Qing; Yao, Yulong; Li, Yali; Wu, Xiaowei; Wang, Chenglong; Yu, Wenwen; Wang, Teng

2017-12-31

The water discharge and sediment load of rivers are changing substantially under the impacts of climate change and human activities, becoming a hot issue in hydro-environmental research. In this study, the water discharge and sediment load in the mainstream and seven tributaries of the Yangtze River were investigated by using long-term hydro-meteorological data from 1953 to 2013. The non-parametric Mann-Kendall test and double mass curve (DMC) were used to detect trends and abrupt change-points in water discharge and sediment load and to quantify the effects of climate change and human activities on water discharge and sediment load. The results are as follows: (1) the water discharge showed a non-significant decreasing trend at most stations except Hukou station. Among these, water discharge at Dongting Lake and the Min River basin shows a significant decreasing trend with average rates of -13.93×10 8 m 3 /year and -1.8×10 8 m 3 /year (PYangtze River. (2) No significant abrupt change-points were detected in the time series of water discharge for all hydrological stations. In contrast, significant abrupt change-points were detected in sediment load, most of these changes appeared in the late 1980s. (3) The water discharge was mainly influenced by precipitation in the Yangtze River basin, whereas sediment load was mainly affected by climate change and human activities; the relative contribution ratios of human activities were above 70% for the Yangtze River. (4) The decrease of sediment load has directly impacted the lower Yangtze River and the delta region. These results will provide a reference for better resource management in the Yangtze River Basin. Copyright © 2017 Elsevier B.V. All rights reserved.

Daily extreme precipitation indices and their impacts on rice yield—A case study over the tropical island in China

Science.gov (United States)

Li, Mao-Fen; Luo, Wei; Li, Hailiang; Liu, Enping; Li, Yuping

2018-04-01

Frequent occurrences of extreme precipitation events have significant impacts on agricultural production. Tropical agriculture has been playing an important role in national economy in China. A precise understanding of variability in extreme precipitation indices and their impacts on crop yields are of great value for farmers and policy makers at county level, particularly in tropical China where almost all agriculture is rainfed. This research has studied observed trends in extreme precipitation indices (a total of 10) during 1988-2013 over Hainan island, tropical China. Mann-Kendall nonparametric test was adopted for trend detection and the results showed that most of precipitation indices showed increasing trend. Since rice is the most important staple food in Hainan island, the impacts of extreme precipitation indices on rice yields were also analyzed through simple correlations. In general, the rainy days and rain intensity in late rice growing season showed increasing trend over Hainan island. The rice yield presented ninth-degree polynomial technological trend at all stations and increasing trend for early rice yield. Late rice yield showed a decreasing trend in some parts of Hainan island. Spearman rank correlation coefficient indicated that the correlation was more pronounced between extreme precipitation indices and yields at Haikou site for early rice, and Haikou, Sanya, and Qionghai stations for late rice, respectively. Further results also indicated that there were statistically significant positive trends of R10 and R20 (number of days with precipitation ≥10 mm and precipitation ≥20 mm, respectively) from July to November at Haikou (located in north of Hainan island), and this positive trend may be a disadvantage for late rice yield. The cut-off value of extreme precipitation indices and its correlation with rice yield anomaly indices for Hainan island provided a foundation for vulnerability assessment as well as a contribution to set up

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

Science.gov (United States)

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

Science.gov (United States)

Goroshi, Sheshakumar; Pradhan, Rohit; Singh, Raghavendra P.; Singh, K. K.; Parihar, Jai Singh

2017-12-01

Owing to the lack of consistent spatial time series data on actual evapotranspiration ( ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite's advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann-Kendall test showed that the domain average ET decreased during the period at a rate of 0.22 mm year^{-1}. A strong decreasing trend (m = -1.75 mm year^{-1}, F = 17.41, P 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (m= -0.320 mm season^{-1} year^{-1}) and post-monsoon period (m= -0.188 mm season^{-1 } year^{-1}). In contrast, an increasing trend was observed during northeast winter monsoon (m = 0.156 mm season^{-1 } year^{-1}) and pre-monsoon (m = 0.068 mm season^{-1 } year^{-1}) periods. Despite an overall net decline in the country, a considerable increase ( 4 mm year^{-1}) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (r >0.5) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (r -0.5) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.

Multi-year levels and trends of non-methane hydrocarbon concentrations observed in ambient air in France

Science.gov (United States)

Waked, Antoine; Sauvage, Stéphane; Borbon, Agnès; Gauduin, Julie; Pallares, Cyril; Vagnot, Marie-Pierre; Léonardis, Thierry; Locoge, Nadine

2016-09-01

Measurements of 31 non-methane hydrocarbons (NMHCs) were carried out at three urban (Paris, 2003-2014, Strasbourg, 2002-2014 and Lyon, 2007-2014) sites in France over the period of a decade. A trend analysis was applied by means of the Mann-Kendall non-parametric test to annual and seasonal mean concentrations in order to point out changes in specific emission sources and to assess the impact of emission controls and reduction strategies. The trends were compared to those from three rural sites (Peyrusse-Vieille, 2002-2013, Tardière, 2003-2013 and Donon, 1997-2007). The results obtained showed a significant yearly decrease in pollutant concentrations over the study period and for the majority of species in the range of -1 to -7% in accordance with the decrease of NMHC emissions in France (-5 to -9%). Concentrations of long-lived species such as ethane and propane which are recognized as tracers of distant sources and natural gas remained constant. Compounds associated with combustion processes such as acetylene, propene, ethylene and benzene showed a significant decline in the range of -2% to -5% yr-1. These trends are consistent with those recently described at urban and background sites in the northern mid-latitudes and with emission inventories. C7-C9 aromatics such as toluene and xylenes as well as C4-C5 alkanes such as isopentane and isobutane also showed a significant decrease in the range of -3% to -7% yr-1. The decreasing trends in terms of % yr-1 observed at these French urban sites were typically higher for acetylene, ethylene and benzene than those reported for French rural sites of the national observatory of Measurement and Evaluation in Rural areas of trans-boundary Air pollution (MERA). The study also highlighted the difficult choice of a long term sampling site representative of the general trends of pollutant concentrations.

Assessing Goodness of Fit in Item Response Theory with Nonparametric Models: A Comparison of Posterior Probabilities and Kernel-Smoothing Approaches

Science.gov (United States)

Sueiro, Manuel J.; Abad, Francisco J.

2011-01-01

The distance between nonparametric and parametric item characteristic curves has been proposed as an index of goodness of fit in item response theory in the form of a root integrated squared error index. This article proposes to use the posterior distribution of the latent trait as the nonparametric model and compares the performance of an index…

An improved nonparametric lower bound of species richness via a modified good-turing frequency formula.

Science.gov (United States)

Chiu, Chun-Huo; Wang, Yi-Ting; Walther, Bruno A; Chao, Anne

2014-09-01

It is difficult to accurately estimate species richness if there are many almost undetectable species in a hyper-diverse community. Practically, an accurate lower bound for species richness is preferable to an inaccurate point estimator. The traditional nonparametric lower bound developed by Chao (1984, Scandinavian Journal of Statistics 11, 265-270) for individual-based abundance data uses only the information on the rarest species (the numbers of singletons and doubletons) to estimate the number of undetected species in samples. Applying a modified Good-Turing frequency formula, we derive an approximate formula for the first-order bias of this traditional lower bound. The approximate bias is estimated by using additional information (namely, the numbers of tripletons and quadrupletons). This approximate bias can be corrected, and an improved lower bound is thus obtained. The proposed lower bound is nonparametric in the sense that it is universally valid for any species abundance distribution. A similar type of improved lower bound can be derived for incidence data. We test our proposed lower bounds on simulated data sets generated from various species abundance models. Simulation results show that the proposed lower bounds always reduce bias over the traditional lower bounds and improve accuracy (as measured by mean squared error) when the heterogeneity of species abundances is relatively high. We also apply the proposed new lower bounds to real data for illustration and for comparisons with previously developed estimators. © 2014, The International Biometric Society.

Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

Directory of Open Access Journals (Sweden)

Ibsen Chivatá Cárdenas

2008-05-01

Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

Detecting runoff variation in Weihe River basin, China

Science.gov (United States)

Jingjing, F.; Qiang, H.; Shen, C.; Aijun, G.

2015-05-01

Dramatic changes in hydrological factors in the Weihe River basin are analysed. These changes have exacerbated ecological problems and caused severe water shortages for agriculture, industries and the human population in the region, but their drivers are uncertain. The Mann-Kendall test, accumulated departure analysis, sequential clustering and the sliding t-test methods were used to identify the causes of changes in precipitation and runoff in the Weihe basin. Change-points were identified in the precipitation and runoff records for all sub-catchments. For runoff, the change in trend was most pronounced during the 1990s, whereas changes in precipitation were more prominent earlier. The results indicate that human activities have had a greater impact than climate change on the hydrology of the Weihe basin. These findings have significant implications for the establishment of effective strategies to counter adverse effects of hydrological changes in the catchment.

Detecting runoff variation in Weihe River basin, China

Directory of Open Access Journals (Sweden)

F. Jingjing

2015-05-01

Full Text Available Dramatic changes in hydrological factors in the Weihe River basin are analysed. These changes have exacerbated ecological problems and caused severe water shortages for agriculture, industries and the human population in the region, but their drivers are uncertain. The Mann-Kendall test, accumulated departure analysis, sequential clustering and the sliding t-test methods were used to identify the causes of changes in precipitation and runoff in the Weihe basin. Change-points were identified in the precipitation and runoff records for all sub-catchments. For runoff, the change in trend was most pronounced during the 1990s, whereas changes in precipitation were more prominent earlier. The results indicate that human activities have had a greater impact than climate change on the hydrology of the Weihe basin. These findings have significant implications for the establishment of effective strategies to counter adverse effects of hydrological changes in the catchment.

Testing isotropy in the local Universe

Energy Technology Data Exchange (ETDEWEB)

Appleby, Stephen; Shafieloo, Arman, E-mail: stephen.appleby@apctp.org, E-mail: arman@apctp.org [Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk 790-784 (Korea, Republic of)

2014-10-01

We test the isotropy of the local distribution of galaxies using the 2MASS extended source catalogue. By decomposing the full sky survey into distinct patches and using a combination of photometric and spectroscopic redshift data, we use both parametric and non-parametric methods to obtain the shape of the luminosity function in each patch. We use the shape of the luminosity function to test the statistical isotropy of the underlying galaxy distribution. The parametric estimator shows some evidence of a hemispherical asymmetry in the north/south Galactic plane. However the non-parametric estimator exhibits no significant anisotropy, with the galaxy distribution being consistent with the assumption of isotropy in all regions considered. The parametric asymmetry is attributed to the relatively poor fit of the functional form to the underlying data. When using the non-parametric estimator, we do find a dipole in the shape of the luminosity function, with maximal deviation from isotropy at galactic coordinate (b,l)=(30{sup o},315{sup o}). However we can ascribe no strong statistical significance to this observation.

Nonparametric estimation of location and scale parameters

KAUST Repository

Potgieter, C.J.

2012-12-01

Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.

Hyperspectral image segmentation using a cooperative nonparametric approach

Science.gov (United States)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

PERAN SELF-REGULATED LEARNING DALAM MEMODERASI PENGGARUH LINGKUNGAN TEMAN SEBAYA DAN MEDIA SOSIAL TERHADAP PRESTASI BELAJAR MATA PELAJARAN AKUNTANSI KOMPUTERSISWA KELAS XI KOMPETENSI KEAHLIAN AKUNTANSI SMK N 1 KENDAL

OpenAIRE

Elsa Puspasari; Agus Wahyudin

2015-01-01

Prestasi belajar komputer akuntansi siswa dipengaruhi oleh beberapa faktor.Dalam penelitian ini faktor yang diduga mempengaruhi prestasi belajar akuntansi adalah lingkungan teman sebaya, media sosial dan Self-Regulated Learning.Masalah dalam penelitian ini berdasarkan hasil observasi awal yang menunjukkan bahwa prestasi belajar komputer akuntansi siswa kelas XI kompetensi keahlian akuntansi SMK N 1 Kendal tergolong rendah.Tujuan penelitian ini adalah untuk mendeskripsikan peran dari Self-Regu...

A SAS macro for testing differences among three or more independent groups using Kruskal-Wallis and Nemenyi tests.

Science.gov (United States)

Liu, Yuewei; Chen, Weihong

2012-02-01

As a nonparametric method, the Kruskal-Wallis test is widely used to compare three or more independent groups when an ordinal or interval level of data is available, especially when the assumptions of analysis of variance (ANOVA) are not met. If the Kruskal-Wallis statistic is statistically significant, Nemenyi test is an alternative method for further pairwise multiple comparisons to locate the source of significance. Unfortunately, most popular statistical packages do not integrate the Nemenyi test, which is not easy to be calculated by hand. We described the theory and applications of the Kruskal-Wallis and Nemenyi tests, and presented a flexible SAS macro to implement the two tests. The SAS macro was demonstrated by two examples from our cohort study in occupational epidemiology. It provides a useful tool for SAS users to test the differences among three or more independent groups using a nonparametric method.

Hermann Günther Graßmann (1809–1877) Visionary Mathematician, Scientist and Neohumanist Scholar : Papers from a Sesquicentennial Conference

CERN Document Server

1996-01-01

In this volume specialists in mathematics, physics, and linguistics present the first comprehensive analysis of the ideas and influence of Hermann G. Graßmann (1809-1877), the remarkable universalist whose work recast the foundations of these disciplines and shaped the course of their modern development.

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

Science.gov (United States)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

International Nuclear Information System (INIS)

David, Hugh

1990-01-01

1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

Non-parametric system identification from non-linear stochastic response

DEFF Research Database (Denmark)

Rüdinger, Finn; Krenk, Steen

2001-01-01

An estimation method is proposed for identification of non-linear stiffness and damping of single-degree-of-freedom systems under stationary white noise excitation. Non-parametric estimates of the stiffness and damping along with an estimate of the white noise intensity are obtained by suitable...... of the energy at mean-level crossings, which yields the damping relative to white noise intensity. Finally, an estimate of the noise intensity is extracted by estimating the absolute damping from the autocovariance functions of a set of modified phase plane variables at different energy levels. The method...

«Vivere da soldato senza essere tale». Gli scritti di guerra di Thomas Mann

Directory of Open Access Journals (Sweden)

Francesca Tucci

2013-11-01

Full Text Available This essay examines the semantic area linked to military activity and in particular the conditions of the soldier in the essays written by Thomas Mann during the First World War. These reconstructions of a historical theme intermix with contributions about current public affairs, and have as their object the events linked to Germany’s entering the war and the general favour with which this was received. Moreover, warlike metaphors tend to slip comfortably into the profound core of Mann’s writing, since they lend themselves rather effectively to descriptions of the artist’s actual aptitudes and duties.

[The influence of Helicobacter pylori infection on the occurance of gastroesophageal reflux in patients with renal insufficiency].

Science.gov (United States)

Stolić, Radojica; Jovanović, Aleksandar; Perić, Vladan; Trajković, Goran; Zivić, Ziva; Stolić, Dragica; Lazarević, Tatjana; Sovtić, Sasa

2007-12-01

Gastric acid is a key factor in the pathophysiology of gastroesophageal reflux disease. A plausible mechanism by which the Helicobacter pylori infection might protect against reflux disease is by its propensity to produce atrophic gastritis. The aim of the study was to establish the influence of Helicobacter pylori infection on the occurrence of gastroesophageal reflux in patients with different stages of renal insufficiency. The examination was organized as a prospective, clinical study and involved 68 patients--33 patients with preterminal stage of renal failure and 35 patients with terminal renal insufficiency. Due to dyspeptic difficulties, in all the patients there was preformed upper esophagogastroscopy and Helicobacter pylori infection was found by ureasa test. The patients with preterminal renal insufficiency were significantly younger than patients with terminal renal failure (53.4 +/- 11.1 vs. 65.4 +/- 12.3 years; p = 0.014). There was found a statistically significant difference between the groups in Helicobacter pylori infection (p = 0.03), hiatal hernia (p = 0.008), gastroesophageal reflux disease (p = 0.007), and duodenal ulcer (p = 0.002). Using the multiple non-parametric correlative analysis there was confirmed a negative correlation between Helicobacter pylori infection and gastro-esophageal reflux disease (Kendal tauB = -0.523; p = 0.003) and hiatal hernia (Kendal tauB = 0.403; p = 0.021), while there was found a positive correlation between gastro-esophageal reflux disease and hiatal hernia (Kendal tauB = 0.350; p = 0.044). Helicobacter pylori infection is a significant protective parameter of the incidence of gastro-esophageal reflux disease in patients with both pre-terminal and terminal renal insufficiency.

The influence of Helicobacter pylori infection on the occurrence of gastroesophageal reflux in patients with renal insufficiency

Directory of Open Access Journals (Sweden)

Stolić Radojica

2007-01-01

Full Text Available Introduction/Aim. Gastric acid is a key factor in the pathophysiology of gastroesophageal reflux disease. A plausible mechanism by which the Helicobacter pylori infection might protect against reflux disease is by its propensity to produce atrophic gastritis. The aim of the study was to establish the influence of Helicobacter pylori infection on the occurrence of gastroesophageal reflux in patients with different stages of renal insufficiency. Methods. The examination was organized as a prospective, clinical study and involved 68 patients − 33 patients with preterminal stage of renal failure and 35 patients with terminal renal insufficiency. Due to dyspeptic difficulties, in all the patients there was preformed upper esophagogastroscopy and Helicobacter pylori infection was found by ureasa test. Results. The patients with preterminal renal insufficiency were significantly younger than patients with terminal renal failure (53.4±11.1 vs. 65.4±12.3 years; p = 0.014. There was found a statistically significant difference between the groups in Helicobacter pylori infection (p = 0.03, hiatal hernia (p = 0.008, gastroesophageal reflux disease (p = 0.007, and duodenal ulcer (p = 0.002. Using the multiple non-parametric correlative analysis there was confirmed a negative correlation between Helicobacter pylori infection and gastro-esophageal reflux disease (Kendal τB = -0.523; p = 0.003 and hiatal hernia (Kendal τB = 0.403; p = 0.021, while there was found a positive correlation between gastro-esophageal reflux disease and hiatal hernia (Kendal τB = 0.350; p = 0.044. Conclusion. Helicobacter pylori infection is a significant protective parameter of the incidence of gastro-esophageal reflux disease in patients with both pre-terminal and terminal renal insufficiency.

The influence of creativity on the process of adaptation in the period of teenagers’ crisis

Directory of Open Access Journals (Sweden)

Chernaya Yu.S.

2017-05-01

Full Text Available this paper studies the influence of regular pictorial creativity class and the environment of creative groups on overcoming the adolescent crisis. Each of 60 students was given a battery of tests. Psychological adaptation, self-esteem and level of aspiration, identity, the subjective sense of loneliness and school anxiety have been studied. The data of descriptive statistics, Mann-Whitney U criterion for nonparametric tests for two independent samples has been processed. It is concluded that adolescents in non-permanent creative groups have a reduced level of neuropsychic adaptation and self-esteem and also high levels of subjective loneliness and frustration in achieving success, compared with adolescents from the constant creative and uncreative groups.

Seasonal Changes of Precipitation and Temperature of Mountainous Watersheds in Future Periods with Approach of Fifth Report of Intergovernmental Panel on Climate Change (Case study: Kashafrood Watershed Basin

Directory of Open Access Journals (Sweden)

Amirhosein Aghakhani Afshar

2017-01-01

Full Text Available Introduction: Hydrology cycle of river basins and water resources availability in arid and semi-arid regions are highly affected by climate changes, so that recently the increase of temperature due to the increase of greenhouse gases have led to anomaly in the Earth’ climate system. At present, General Circulation Models (GCMs are the most frequently used models for projection of different climatic change scenarios. Up to now, IPCC has released four different versions of GCM models, including First Assessment Report models (FAR in 1990, Second Assessment Report models (SAR in 1996, Third Assessment Report models (TAR in 2001 and Fourth Assessment Report models (AR4 in 2007. In 2011, new generation of GCM, known as phase five of the Coupled Model Intercomparison Project (CMIP5 released which it has been actively participated in the preparation of Intergovernmental Panel on Climate Change (IPCC fifth Assessment report (AR5. A set of experiments such as simulations of 20th and projections of 21st century climate under the new emission scenarios (so called Representative Concentration Pathways (RCPs are included in CMIP5. Iran is a country that located in arid and semi-arid climates mostly characterized by low rainfall and high temperature. Anomalies in precipitation and temperature in Iran play a significant role in this agricultural and quickly developing country. Growing population, extensive urbanization and rapid economic development shows that Iran faces intensive challenges in available water resources at present and especially in the future. The first purpose of this study is to analyze the seasonal trends of future climate components over the Kashafrood Watershed Basin (KWB located in the northeastern part of Iran and in the Khorsan-e Razavi province using fifth report of Intergovernmental Panel on climate change (IPCC under new emission scenarios with Mann-Kendall (MK test. Mann-Kendall is one of the most commonly used nonparametric

Differences between early and late onset adult depression

DEFF Research Database (Denmark)

Drachmann Bukh, Jens; Bock, Camilla; Vinberg, Maj

2011-01-01

episode depression were systematically recruited. Characteristics including psychiatric co-morbidity, personality disorders and traits, stressful life events prior to onset, family history, and treatment outcome were assessed by structured interviews and compared by chi-square tests for categorical data...... prevalence of co-morbid personality disorders, higher levels of neuroticism, and a lower prevalence of stressful life events preceding onset compared to patients with later age-of-onset. There were no differences in severity of the depressive episode, treatment outcome or family loading of psychiatric......, t-tests for continuous parametric data and Mann-Whitney U-test for continuous nonparametric data. Logistic and multiple regression analyses were used to adjust the analyses for potentially confounding variables. Results: Patients with early onset of depression were characterised by a higher...

Nonparametric inference of network structure and dynamics

Science.gov (United States)

Peixoto, Tiago P.

The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among

Visit of the ATLAS cavern by Prof. Murray Gell-Mann, Physics Nobel 1969. With Dr Peter Jenni and Dr Alison Lister

CERN Multimedia

Maximilien Brice

2012-01-01

Murray Gell-Mann, well known for proposing the quark model and as a recipient of the Nobel Prize in Physics in 1969, came to CERN on 23 January. During his visit he gave a theoretical physics seminar on decoherent histories in quantum mechanics.

An Analysis on the Images of the Devils in the Works of Geothe, Bulgakov and Thomas Mann

Directory of Open Access Journals (Sweden)

Jie CHANG

2013-10-01

Full Text Available Starting from the analysis on the devils in the Bible stories, the writer of this article makes an analysis on Mephistopheles in Faust by JohannEolfgang von Goethe (1749-1832 Woland in The Master and Margarita by Mikhaíl Afanasyevich Bulgakov (1891-1940, and a Mephistopheles figure in Doctor Faustus by Thomas Mann (1875-1955. The origin, characteristics and changes of the images of these devils shall be discussed in this article.

The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models

OpenAIRE

GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.

2008-01-01

In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.

Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches

OpenAIRE

Wang, Wenshuo; Xi, Junqiang; Zhao, Ding

2017-01-01

Analysis and recognition of driving styles are profoundly important to intelligent transportation and vehicle calibration. This paper presents a novel driving style analysis framework using the primitive driving patterns learned from naturalistic driving data. In order to achieve this, first, a Bayesian nonparametric learning method based on a hidden semi-Markov model (HSMM) is introduced to extract primitive driving patterns from time series driving data without prior knowledge of the number...

Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

OpenAIRE

Li, Zhanchao; Gu, Chongshi; Wu, Zhongru

2013-01-01

The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model ...

Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.

Science.gov (United States)

Rodríguez-Álvarez, María Xosé; Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Tahoces, Pablo G

2018-03-01

Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.

A non-parametric framework for estimating threshold limit values

Directory of Open Access Journals (Sweden)

Ulm Kurt

2005-11-01

Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis

Science.gov (United States)

Hof, Stefanie

2014-01-01

Private tutoring has become popular throughout the world. However, evidence for the effect of private tutoring on students' academic outcome is inconclusive; therefore, this paper presents an alternative framework: a nonparametric bounds method. The present examination uses, for the first time, a large representative data-set in a European setting…

Data analysis with small samples and non-normal data nonparametrics and other strategies

CERN Document Server

Siebert, Carl F

2017-01-01

Written in everyday language for non-statisticians, this book provides all the information needed to successfully conduct nonparametric analyses. This ideal reference book provides step-by-step instructions to lead the reader through each analysis, screenshots of the software and output, and case scenarios to illustrate of all the analytic techniques.

Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach

International Nuclear Information System (INIS)

Wang, H.; Ang, B.W.; Wang, Q.W.; Zhou, P.

2017-01-01

Evaluating economy-wide energy performance is an integral part of assessing the effectiveness of a country's energy efficiency policy. Non-parametric frontier approach has been widely used by researchers for such a purpose. This paper proposes an extended non-parametric frontier approach to studying economy-wide energy efficiency and productivity performances by accounting for sectoral heterogeneity. Relevant techniques in index number theory are incorporated to quantify the driving forces behind changes in the economy-wide energy productivity index. The proposed approach facilitates flexible modelling of different sectors' production processes, and helps to examine sectors' impact on the aggregate energy performance. A case study of China's economy-wide energy efficiency and productivity performances in its 11th five-year plan period (2006–2010) is presented. It is found that sectoral heterogeneities in terms of energy performance are significant in China. Meanwhile, China's economy-wide energy productivity increased slightly during the study period, mainly driven by the technical efficiency improvement. A number of other findings have also been reported. - Highlights: • We model economy-wide energy performance by considering sectoral heterogeneity. • The proposed approach can identify sectors' impact on the aggregate energy performance. • Obvious sectoral heterogeneities are identified in evaluating China's energy performance.

rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

Science.gov (United States)

Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

2015-07-01

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Nedostatečnost ve světle měšťanské epochy: Thomas Mann a Hugo von Hofmannsthal // Inadequacy in the light of the bourgeois age — Thomas Mann and Hugo von Hofmannsthal

Directory of Open Access Journals (Sweden)

Štěpán Sirovátka

2015-10-01

Full Text Available The paper aims to compare two authors of the Fin-de-Siècle from the German-speaking area (Thomas Mann and Hugo von Hofmannsthal and tries to offer a specific “German” interpretation of contemporary phenomena like dandyism or estheticism. For the German area, Mann’s concept of the bourgeoisie as a spiritual form of life appears to be relevant. It is the idea of the middle way denying any sort of excess and connected with moral obligation. Therefore, German “decadence” is lacking an explicit anti-social gesture (dandyism and is merely the expression of the process of “Entbürgerlichung”.

Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

Science.gov (United States)

Siciliani, Luigi

2006-01-01

Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

Adaptive nonparametric estimation for L\\'evy processes observed at low frequency

OpenAIRE

Kappus, Johanna

2013-01-01

This article deals with adaptive nonparametric estimation for L\\'evy processes observed at low frequency. For general linear functionals of the L\\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of convergence under regularity assumptions. Our focus lies on the adaptive choice of the bandwidth, using model selection techniques. We face here a non-standard problem of model selection with unknown variance. A new approach towards this problem is proposed, ...

Testing the Weak Form Efficiency of Karachi Stock Exchange

Directory of Open Access Journals (Sweden)

Muhammad Arshad Haroon

2012-12-01

Full Text Available In an efficient market, share prices reflect all available information. The study of efficient market hypothesis helps to take right decisions related to investments. In this research,weak form efficiency has been tested of Karachi Stock Exchange—KSE covering the period of 2nd November 1991 to 2nd November 2011. Descriptive statistics indicated the absence of weak form efficiency while results of non-parametric tests, showed consistency as well. We employed non-parametric tests were KS Goodness-of-Fit test,run test and autocorrelation test to find out serial independency of the data. Results prove that KSE is not weak-form-efficient. This happens because KSE is an emerging market and there, it has been observed that information take time to be processed. Thus it can besaid that technical analysis may be applied to gain abnormal returns.

A nonparametric statistical method for determination of a confidence interval for the mean of a set of results obtained in a laboratory intercomparison

International Nuclear Information System (INIS)

Veglia, A.

1981-08-01

In cases where sets of data are obviously not normally distributed, the application of a nonparametric method for the estimation of a confidence interval for the mean seems to be more suitable than some other methods because such a method requires few assumptions about the population of data. A two-step statistical method is proposed which can be applied to any set of analytical results: elimination of outliers by a nonparametric method based on Tchebycheff's inequality, and determination of a confidence interval for the mean by a non-parametric method based on binominal distribution. The method is appropriate only for samples of size n>=10

Two non-parametric methods for derivation of constraints from radiotherapy dose–histogram data

International Nuclear Information System (INIS)

Ebert, M A; Kennedy, A; Joseph, D J; Gulliford, S L; Buettner, F; Foo, K; Haworth, A; Denham, J W

2014-01-01

Dose constraints based on histograms provide a convenient and widely-used method for informing and guiding radiotherapy treatment planning. Methods of derivation of such constraints are often poorly described. Two non-parametric methods for derivation of constraints are described and investigated in the context of determination of dose-specific cut-points—values of the free parameter (e.g., percentage volume of the irradiated organ) which best reflect resulting changes in complication incidence. A method based on receiver operating characteristic (ROC) analysis and one based on a maximally-selected standardized rank sum are described and compared using rectal toxicity data from a prostate radiotherapy trial. Multiple test corrections are applied using a free step-down resampling algorithm, which accounts for the large number of tests undertaken to search for optimal cut-points and the inherent correlation between dose–histogram points. Both methods provide consistent significant cut-point values, with the rank sum method displaying some sensitivity to the underlying data. The ROC method is simple to implement and can utilize a complication atlas, though an advantage of the rank sum method is the ability to incorporate all complication grades without the need for grade dichotomization. (note)

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

Science.gov (United States)

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Statistical trend analysis methods for temporal phenomena

Energy Technology Data Exchange (ETDEWEB)

Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)

1997-04-01

We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.

Statistical trend analysis methods for temporal phenomena

International Nuclear Information System (INIS)

Lehtinen, E.; Pulkkinen, U.; Poern, K.

1997-04-01

We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods

The Implication of Climate Signal for Precipitation in the Heihe River Basin, Northwest China

Directory of Open Access Journals (Sweden)

Fei Wang

2016-01-01

Full Text Available This paper studies the stochastic dynamic variability of precipitation, for the upper, middle, and lower reaches of the Heihe River basin in Northwest China, by employing Mann-Kendall statistic, Pettitt test, and wavelet transform methods. The possible associations with three prominent climatic patterns, El Niño-Southern Oscillation (ENSO, Artic Oscillation (AO, and Indian Ocean Dipole (IOD, are examined by using multiscale wavelet coherence method. No significant trend is identified for the interannual precipitation variability. However, about 2-year significant variability is detected for the lower reach of the Heihe River basin, and this dominating precipitation variability is essentially depicted by AO. The possible influences of ENSO are exerted on long-term timescale, 8–16 years. The obtained knowledge is helpful for the predications of extreme hydroclimatological events and better reservoir operations for regional water resources.

Revealed preference tests for collective household behavior

NARCIS (Netherlands)

Cherchye, L.J.H.; de Rock, B.; Vermeulen, F.M.P.; Verriest, E.; Molina, J.A.

2011-01-01

This chapter contains a state of the art of revealed preference tests for consistency of observed household behavior with Pareto efficiency. These tests are entirely nonparametric, since they do not require any assumptions regarding the parametric form of individual preferences or the intrahousehold

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

DEFF Research Database (Denmark)

Tan, Qihua; Thomassen, Mads; Burton, Mark

2017-01-01

the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

MEASURING DARK MATTER PROFILES NON-PARAMETRICALLY IN DWARF SPHEROIDALS: AN APPLICATION TO DRACO

International Nuclear Information System (INIS)

Jardel, John R.; Gebhardt, Karl; Fabricius, Maximilian H.; Williams, Michael J.; Drory, Niv

2013-01-01

We introduce a novel implementation of orbit-based (or Schwarzschild) modeling that allows dark matter density profiles to be calculated non-parametrically in nearby galaxies. Our models require no assumptions to be made about velocity anisotropy or the dark matter profile. The technique can be applied to any dispersion-supported stellar system, and we demonstrate its use by studying the Local Group dwarf spheroidal galaxy (dSph) Draco. We use existing kinematic data at larger radii and also present 12 new radial velocities within the central 13 pc obtained with the VIRUS-W integral field spectrograph on the 2.7 m telescope at McDonald Observatory. Our non-parametric Schwarzschild models find strong evidence that the dark matter profile in Draco is cuspy for 20 ≤ r ≤ 700 pc. The profile for r ≥ 20 pc is well fit by a power law with slope α = –1.0 ± 0.2, consistent with predictions from cold dark matter simulations. Our models confirm that, despite its low baryon content relative to other dSphs, Draco lives in a massive halo.

Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements

KAUST Repository

Ryu, Duchwan

2010-09-28

We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.

Panel data nonparametric estimation of production risk and risk preferences

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

approaches for obtaining firm-specific measures of risk attitudes. We found that Polish dairy farmers are risk averse regarding production risk and price uncertainty. According to our results, Polish dairy farmers perceive the production risk as being more significant than the risk related to output price......We apply nonparametric panel data kernel regression to investigate production risk, out-put price uncertainty, and risk attitudes of Polish dairy farms based on a firm-level unbalanced panel data set that covers the period 2004–2010. We compare different model specifications and different...

Multi-Directional Non-Parametric Analysis of Agricultural Efficiency

DEFF Research Database (Denmark)

Balezentis, Tomas

This thesis seeks to develop methodologies for assessment of agricultural efficiency and employ them to Lithuanian family farms. In particular, we focus on three particular objectives throughout the research: (i) to perform a fully non-parametric analysis of efficiency effects, (ii) to extend...... to the Multi-Directional Efficiency Analysis approach when the proposed models were employed to analyse empirical data of Lithuanian family farm performance, we saw substantial differences in efficiencies associated with different inputs. In particular, assets appeared to be the least efficiently used input...... relative to labour, intermediate consumption and land (in some cases land was not treated as a discretionary input). These findings call for further research on relationships among financial structure, investment decisions, and efficiency in Lithuanian family farms. Application of different techniques...

A multitemporal and non-parametric approach for assessing the impacts of drought on vegetation greenness

DEFF Research Database (Denmark)

Carrao, Hugo; Sepulcre, Guadalupe; Horion, Stéphanie Marie Anne F

2013-01-01

This study evaluates the relationship between the frequency and duration of meteorological droughts and the subsequent temporal changes on the quantity of actively photosynthesizing biomass (greenness) estimated from satellite imagery on rainfed croplands in Latin America. An innovative non-parametric...... and non-supervised approach, based on the Fisher-Jenks optimal classification algorithm, is used to identify multi-scale meteorological droughts on the basis of empirical cumulative distributions of 1, 3, 6, and 12-monthly precipitation totals. As input data for the classifier, we use the gridded GPCC...... for the period between 1998 and 2010. The time-series analysis of vegetation greenness is performed during the growing season with a non-parametric method, namely the seasonal Relative Greenness (RG) of spatially accumulated fAPAR. The Global Land Cover map of 2000 and the GlobCover maps of 2005/2006 and 2009...

A Bayesian nonparametric approach to causal inference on quantiles.

Science.gov (United States)

Xu, Dandan; Daniels, Michael J; Winterstein, Almut G

2018-02-25

We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.

Bayesian nonparametric meta-analysis using Polya tree mixture models.

Science.gov (United States)

Branscum, Adam J; Hanson, Timothy E

2008-09-01

Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

Science.gov (United States)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

Debt and growth: A non-parametric approach

Science.gov (United States)

Brida, Juan Gabriel; Gómez, David Matesanz; Seijas, Maria Nela

2017-11-01

In this study, we explore the dynamic relationship between public debt and economic growth by using a non-parametric approach based on data symbolization and clustering methods. The study uses annual data of general government consolidated gross debt-to-GDP ratio and gross domestic product for sixteen countries between 1977 and 2015. Using symbolic sequences, we introduce a notion of distance between the dynamical paths of different countries. Then, a Minimal Spanning Tree and a Hierarchical Tree are constructed from time series to help detecting the existence of groups of countries sharing similar economic performance. The main finding of the study appears for the period 2008-2016 when several countries surpassed the 90% debt-to-GDP threshold. During this period, three groups (clubs) of countries are obtained: high, mid and low indebted countries, suggesting that the employed debt-to-GDP threshold drives economic dynamics for the selected countries.