Genetic variants influencing phenotypic variance heterogeneity.

Science.gov (United States)

Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa

2018-03-01

Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.

Significant population genetic structure detected in the rock bream Oplegnathus fasciatus (Temminck & Schlegel, 1844) inferred from fluorescent-AFLP analysis

Science.gov (United States)

Xiao, Yongshuang; Ma, Daoyuan; Xu, Shihong; Liu, Qinghua; Wang, Yanfeng; Xiao, Zhizhong; Li, Jun

2016-05-01

Oplegnathus fasciatus (rock bream) is a commercial rocky reef fish species in East Asia that has been considered for aquaculture. We estimated the population genetic diversity and population structure of the species along the coastal waters of China using fluorescent-amplified fragment length polymorphisms technology. Using 53 individuals from three populations and four pairs of selective primers, we amplified 1 264 bands, 98.73% of which were polymorphic. The Zhoushan population showed the highest Nei's genetic diversity and Shannon genetic diversity. The results of analysis of molecular variance (AMOVA) showed that 59.55% of genetic variation existed among populations and 40.45% occurred within populations, which indicated that a significant population genetic structure existed in the species. The pairwise fixation index F st ranged from 0.20 to 0.63 and were significant after sequential Bonferroni correction. The topology of an unweighted pair group method with arithmetic mean tree showed two significant genealogical branches corresponding to the sampling locations of North and South China. The AMOVA and STRUCTURE analyses suggested that the O. fasciatus populations examined should comprise two stocks.

Means and Variances without Calculus

Science.gov (United States)

Kinney, John J.

2005-01-01

This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

Downside Variance Risk Premium

OpenAIRE

Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric

2015-01-01

We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...

Analysis of genetic structure in Melia volkensii (Gurke.) populations ...

African Journals Online (AJOL)

Administrator

2Farm Forestry Programme, Kenya Forestry Research Institute, P. O. Box 20412, Nairobi, Kenya. Accepted 5 ... were used to estimate genetic distances between populations and for construction of neighbour-joining phenograms. Analysis of Molecular Variance (AMOVA) indicated significant genetic differentiation between ...

Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

Science.gov (United States)

Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

Towards a mathematical foundation of minimum-variance theory

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)

2002-08-30

The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)

Minimum Variance Portfolios in the Brazilian Equity Market

Directory of Open Access Journals (Sweden)

Alexandre Rubesam

2013-03-01

Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2014-01-01

Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.

Science.gov (United States)

Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil

2011-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.

CMB-S4 and the hemispherical variance anomaly

Science.gov (United States)

O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

2017-09-01

Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

Estimation of measurement variances

International Nuclear Information System (INIS)

Anon.

1981-01-01

In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

Simulation study on heterogeneous variance adjustment for observations with different measurement error variance

DEFF Research Database (Denmark)

Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander

2013-01-01

of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...

Approximate zero-variance Monte Carlo estimation of Markovian unreliability

International Nuclear Information System (INIS)

Delcoux, J.L.; Labeau, P.E.; Devooght, J.

1997-01-01

Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

A Mean variance analysis of arbitrage portfolios

Science.gov (United States)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Mean-Variance Optimization in Markov Decision Processes

OpenAIRE

Mannor, Shie; Tsitsiklis, John N.

2011-01-01

We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.

A COSMIC VARIANCE COOKBOOK

International Nuclear Information System (INIS)

Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.

2011-01-01

Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic

Genetic structure and diversity of the Neem Germplasm Bank from ...

African Journals Online (AJOL)

Particular

2013-05-15

May 15, 2013 ... ... fragment length polymorphism; AMOVA, molecular variance analysis. ... are technically simple, suitable for large-scale germplasm ... Brazil, our study aims to evaluate the genetic structure and genetic ... voltage of 100 V for 90 min. Gel was .... which does not justify an extra effort in labor (Bekessy et.

MCNP variance reduction overview

International Nuclear Information System (INIS)

Hendricks, J.S.; Booth, T.E.

1985-01-01

The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code

Estimating High-Frequency Based (Co-) Variances: A Unified Approach

DEFF Research Database (Denmark)

Voev, Valeri; Nolte, Ingmar

We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...

Estimating quadratic variation using realized variance

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....

Gini estimation under infinite variance

NARCIS (Netherlands)

A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)

2018-01-01

textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient

Using variances to comply with resource conservation and recovery act treatment standards

International Nuclear Information System (INIS)

Ranek, N.L.

2002-01-01

When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.

Comparing estimates of genetic variance across different relationship models.

Science.gov (United States)

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong

2009-04-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

Energy Technology Data Exchange (ETDEWEB)

Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2006-07-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

International Nuclear Information System (INIS)

Christoforou, S.; Hoogenboom, J. E.

2006-01-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

The Genealogical Consequences of Fecundity Variance Polymorphism

Science.gov (United States)

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

Variance analysis of forecasted streamflow maxima in a wet temperate climate

Science.gov (United States)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Host nutrition alters the variance in parasite transmission potential.

Science.gov (United States)

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

Efficient Cardinality/Mean-Variance Portfolios

OpenAIRE

Brito, R. Pedro; Vicente, Luís Nunes

2014-01-01

International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...

Some novel inequalities for fuzzy variables on the variance and its rational upper bound

Directory of Open Access Journals (Sweden)

Xiajie Yi

2016-02-01

Full Text Available Abstract Variance is of great significance in measuring the degree of deviation, which has gained extensive usage in many fields in practical scenarios. The definition of the variance on the basis of the credibility measure was first put forward in 2002. Following this idea, the calculation of the accurate value of the variance for some special fuzzy variables, like the symmetric and asymmetric triangular fuzzy numbers and the Gaussian fuzzy numbers, is presented in this paper, which turns out to be far more complicated. Thus, in order to better implement variance in real-life projects like risk control and quality management, we suggest a rational upper bound of the variance based on an inequality, together with its calculation formula, which can largely simplify the calculation process within a reasonable range. Meanwhile, some discussions between the variance and its rational upper bound are presented to show the rationality of the latter. Furthermore, two inequalities regarding the rational upper bound of variance and standard deviation of the sum of two fuzzy variables and their individual variances and standard deviations are proved. Subsequently, some numerical examples are illustrated to show the effectiveness and the feasibility of the proposed inequalities.

A geometric approach to multiperiod mean variance optimization of assets and liabilities

OpenAIRE

Leippold, Markus; Trojani, Fabio; Vanini, Paolo

2005-01-01

We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the corresponding multi period mean variance frontiers are spanned by an orthogonal basis of dynamic returns. Spec...

Coupled bias-variance tradeoff for cross-pose face recognition.

Science.gov (United States)

Li, Annan; Shan, Shiguang; Gao, Wen

2012-01-01

Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

Variance in parametric images: direct estimation from parametric projections

International Nuclear Information System (INIS)

Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

2000-01-01

Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

Science.gov (United States)

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Approximation errors during variance propagation

International Nuclear Information System (INIS)

Dinsmore, Stephen

1986-01-01

Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given

Realized Variance and Market Microstructure Noise

DEFF Research Database (Denmark)

Hansen, Peter R.; Lunde, Asger

2006-01-01

We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...

The Impact of Jump Distributions on the Implied Volatility of Variance

DEFF Research Database (Denmark)

Nicolato, Elisa; Pisani, Camilla; Pedersen, David Sloth

2017-01-01

We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider both realized variance options and VIX options, and we examine the impact of the distribution...... of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...

Genetic determinism and evolutionary reconstruction of a host jump in a plant virus

DEFF Research Database (Denmark)

Vassilakos, Nikon; Simon, Vincent; Tzima, Aliki

2016-01-01

In spite of their widespread occurrence, only few host jumps by plant viruses have been evidenced and the molecular bases of even fewer have been determined. A combination of three independent approaches, 1) experimental evolution followed by reverse genetics analysis, 2) positive selection...... analysis, and 3) locus-by-locus analysis of molecular variance (AMOVA) allowed reconstructing the Potato virus Y (PVY; genus Potyvirus, family Potyviridae) jump to pepper (Capsicum annuum), probably from other solanaceous plants. Synthetic chimeras between infectious cDNA clones of two PVY isolates...... independently and conferred adaptation to C. annuum. In addition to increasing our knowledge of host jumps in plant viruses, this study illustrates also the efficiency of locus-by-locus AMOVA and combined approaches to identify adaptive mutations in the genome of RNA viruses....

Confidence Interval Approximation For Treatment Variance In ...

African Journals Online (AJOL)

In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...

A class of multi-period semi-variance portfolio for petroleum exploration and development

Science.gov (United States)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

A Visual Model for the Variance and Standard Deviation

Science.gov (United States)

Orris, J. B.

2011-01-01

This paper shows how the variance and standard deviation can be represented graphically by looking at each squared deviation as a graphical object--in particular, as a square. A series of displays show how the standard deviation is the size of the average square.

Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.

Science.gov (United States)

Nelson, Ronald M; Pettersson, Mats E; Li, Xidan; Carlborg, Örjan

2013-01-01

Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.

Regime shifts in mean-variance efficient frontiers: some international evidence

OpenAIRE

Massimo Guidolin; Federica Ria

2010-01-01

Regime switching models have been assuming a central role in financial applications because of their well-known ability to capture the presence of rich non-linear patterns in the joint distribution of asset returns. This paper examines how the presence of regimes in means, variances, and correlations of asset returns translates into explicit dynamics of the Markowitz mean-variance frontier. In particular, the paper shows both theoretically and through an application to international equity po...

Genetic diversity and environmental associations of sacsaoul ( Haloxylon ammodendron)

Science.gov (United States)

Zhang, Linjing; Zhao, Guifang; Yue, Ming; Pan, Xiaoling

2003-07-01

Random amplified polymorphic DNA (RAPD) markers were used to assess levels and patterns of genetic diversity in H. ammodendron (Chenopodiaceae). A total of 117 plants from 6 subpopulations on oasis-desert ecotone was analyzed by 16 arbitrarily chosen primers resulting in highly reproducible RAPD bands. The analysis of molecular variance (AMOVA) with distances among individuals showed that most of the variation (74%) occurred among individuals within subpopulations, which is expected for a crossing organism, and 26% of variation among subpopulations. Estimates of Shannon index and Nei"s index from allele frequencies corroborated AMOVA partitioning in H. ammodendron. UPGMA cluster analyses, based on genetic distance, do not revealed grouping of some geographically proximate populations. This is the first report of the partitioning of genetic variability within and between subpopulations of H. ammodendron and provides important baseline data for optimizing sampling strategies and for conserving the genetic resources of this species. The Percentage of polymorphic loci was as high as 96%, presumably being response to oasis-desert ecotone. There were gene flows (Nm=5.38 individuals/generation), based on gene differentiation coefficient (GST was 0.1567) between subpopulations, and strong habitat selection override the gene flow to maintain the subpopulation differentiation. Correlation analyses showed that there was significant relationship between genetic diversity and soil CL ion.

Least-squares variance component estimation

NARCIS (Netherlands)

Teunissen, P.J.G.; Amiri-Simkooei, A.R.

2007-01-01

Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight

Markov switching mean-variance frontier dynamics: theory and international evidence

OpenAIRE

M. Guidolin; F. Ria

2010-01-01

It is well-known that regime switching models are able to capture the presence of rich non-linear patterns in the joint distribution of asset returns. After reviewing key concepts and technical issues related to specifying, estimating, and using multivariate Markov switching models in financial applications, in this paper we map the presence of regimes in means, variances, and covariances of asset returns into explicit dynamics of the Markowitz mean-variance frontier. In particular, we show b...

Within-category variance and lexical tone discrimination in native and non-native speakers

NARCIS (Netherlands)

Hoffmann, C.W.G.; Sadakata, M.; Chen, A.; Desain, P.W.M.; McQueen, J.M.; Gussenhove, C.; Chen, Y.; Dediu, D.

2014-01-01

In this paper, we show how acoustic variance within lexical tones in disyllabic Mandarin Chinese pseudowords affects discrimination abilities in both native and non-native speakers of Mandarin Chinese. Within-category acoustic variance did not hinder native speakers in discriminating between lexical

Motor equivalence and structure of variance: multi-muscle postural synergies in Parkinson's disease.

Science.gov (United States)

Falaki, Ali; Huang, Xuemei; Lewis, Mechelle M; Latash, Mark L

2017-07-01

We explored posture-stabilizing multi-muscle synergies with two methods of analysis of multi-element, abundant systems: (1) Analysis of inter-cycle variance; and (2) Analysis of motor equivalence, both quantified within the framework of the uncontrolled manifold (UCM) hypothesis. Data collected in two earlier studies of patients with Parkinson's disease (PD) were re-analyzed. One study compared synergies in the space of muscle modes (muscle groups with parallel scaling of activation) during tasks performed by early-stage PD patients and controls. The other study explored the effects of dopaminergic medication on multi-muscle-mode synergies. Inter-cycle variance and absolute magnitude of the center of pressure displacement across consecutive cycles were quantified during voluntary whole-body sway within the UCM and orthogonal to the UCM space. The patients showed smaller indices of variance within the UCM and motor equivalence compared to controls. The indices were also smaller in the off-drug compared to on-drug condition. There were strong across-subject correlations between the inter-cycle variance within/orthogonal to the UCM and motor equivalent/non-motor equivalent displacements. This study has shown that, at least for cyclical tasks, analysis of variance and analysis of motor equivalence lead to metrics of stability that correlate with each other and show similar effects of disease and medication. These results show, for the first time, intimate links between indices of variance and motor equivalence. They suggest that analysis of motor equivalence, which requires only a handful of trials, could be used broadly in the field of motor disorders to analyze problems with action stability.

A study of heterogeneity of environmental variance for slaughter weight in pigs

DEFF Research Database (Denmark)

Ibánez-Escriche, N; Varona, L; Sorensen, D

2008-01-01

This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...

UV spectral fingerprinting and analysis of variance-principal component analysis: a useful tool for characterizing sources of variance in plant materials.

Science.gov (United States)

Luthria, Devanand L; Mukhopadhyay, Sudarsan; Robbins, Rebecca J; Finley, John W; Banuelos, Gary S; Harnly, James M

2008-07-23

UV spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), can differentiate between cultivars and growing conditions (or treatments) and can be used to identify sources of variance. Broccoli samples, composed of two cultivars, were grown under seven different conditions or treatments (four levels of Se-enriched irrigation waters, organic farming, and conventional farming with 100 and 80% irrigation based on crop evaporation and transpiration rate). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired for the UV region (220-380 nm) using a 50-fold dilution of the extract. ANOVA-PCA was used to construct subset matrices that permitted easy verification of the hypothesis that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show that cultivar, treatment, and analytical repeatability contributed 30.5, 68.3, and 1.2% of the variance, respectively.

Use of genomic models to study genetic control of environmental variance

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

How the Weak Variance of Momentum Can Turn Out to be Negative

Science.gov (United States)

Feyereisen, M. R.

2015-05-01

Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

Speed Variance and Its Influence on Accidents.

Science.gov (United States)

Garber, Nicholas J.; Gadirau, Ravi

A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

The mean and variance of phylogenetic diversity under rarefaction.

Science.gov (United States)

Nipperess, David A; Matsen, Frederick A

2013-06-01

Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

OpenAIRE

Röring, Johan

2017-01-01

Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...

Genetic control of residual variance of yearling weight in Nellore beef cattle.

Science.gov (United States)

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

Science.gov (United States)

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.T.

1999-01-01

The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)

Estimation of (co)variances for genomic regions of flexible sizes

DEFF Research Database (Denmark)

Sørensen, Lars P; Janss, Luc; Madsen, Per

2012-01-01

was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. CONCLUSIONS: The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances......BACKGROUND: Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related...... with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level...

Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

Science.gov (United States)

Lebigre, Christophe; Arcese, Peter; Reid, Jane M

2013-07-01

Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased

VARIANCE COMPONENTS AND SELECTION FOR FEATHER PECKING BEHAVIOR IN LAYING HENS

OpenAIRE

Su, Guosheng; Kjaer, Jørgen B.; Sørensen, Poul

2005-01-01

Variance components and selection response for feather pecking behaviour were studied by analysing the data from a divergent selection experiment. An investigation show that a Box-Cox transformation with power =-0.2 made the data be approximately normally distributed and fit best by the given model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the two traits in both low feather peckin...

Dynamic Mean-Variance Asset Allocation

OpenAIRE

Basak, Suleyman; Chabakauri, Georgy

2009-01-01

Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

The Variance Composition of Firm Growth Rates

Directory of Open Access Journals (Sweden)

Luiz Artur Ledur Brito

2009-04-01

Full Text Available Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample.

Variability of indoor and outdoor VOC measurements: An analysis using variance components

International Nuclear Information System (INIS)

Jia, Chunrong; Batterman, Stuart A.; Relyea, George E.

2012-01-01

This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory. - Highlights: ► The variability of VOC measurements was partitioned using nested analysis. ► Indoor VOCs were primarily controlled by seasonal and residence effects. ► Outdoor VOC levels were homogeneous within neighborhoods. ► Measurement uncertainty was high for many outdoor VOCs. ► Variance component analysis is useful for designing effective sampling programs. - Indoor VOC concentrations were primarily controlled by seasonal and residence effects; and outdoor concentrations were homogeneous within neighborhoods. Variance component analysis is a useful tool for designing effective sampling programs.

Mixed emotions: Sensitivity to facial variance in a crowd of faces.

Science.gov (United States)

Haberman, Jason; Lee, Pegan; Whitney, David

2015-01-01

The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

Towards the ultimate variance-conserving convection scheme

International Nuclear Information System (INIS)

Os, J.J.A.M. van; Uittenbogaard, R.E.

2004-01-01

In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287

Gender variance in childhood and sexual orientation in adulthood: a prospective study.

Science.gov (United States)

Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

2013-11-01

Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in

The variance of the locally measured Hubble parameter explained with different estimators

DEFF Research Database (Denmark)

Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

2017-01-01

We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

Variance estimation for sensitivity analysis of poverty and inequality measures

Directory of Open Access Journals (Sweden)

Christian Dudel

2017-04-01

Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.

Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans

Science.gov (United States)

Raju, C.; Vidya, R.

2016-06-01

In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.

Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.

Science.gov (United States)

Diaz, S Anaid; Viney, Mark

2014-06-01

Organisms live in heterogeneous environments, so strategies that maximze fitness in such environments will evolve. Variation in traits is important because it is the raw material on which natural selection acts during evolution. Phenotypic variation is usually thought to be due to genetic variation and/or environmentally induced effects. Therefore, genetically identical individuals in a constant environment should have invariant traits. Clearly, genetically identical individuals do differ phenotypically, usually thought to be due to stochastic processes. It is now becoming clear, especially from studies of unicellular species, that phenotypic variance among genetically identical individuals in a constant environment can be genetically controlled and that therefore, in principle, this can be subject to selection. However, there has been little investigation of these phenomena in multicellular species. Here, we have studied the mean lifetime fecundity (thus a trait likely to be relevant to reproductive success), and variance in lifetime fecundity, in recently-wild isolates of the model nematode Caenorhabditis elegans. We found that these genotypes differed in their variance in lifetime fecundity: some had high variance in fecundity, others very low variance. We find that this variance in lifetime fecundity was negatively related to the mean lifetime fecundity of the lines, and that the variance of the lines was positively correlated between environments. We suggest that the variance in lifetime fecundity may be a bet-hedging strategy used by this species.

Discrete and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

Genetic variability of Pantaneiro horse using RAPD-PCR markers

OpenAIRE

Egito,Andréa Alves do; Fuck,Beatriz Helena; McManus,Concepta; Paiva,Samuel Rezende; Albuquerque,Maria do Socorro Maués; Santos,Sandra Aparecida; Abreu,Urbano Gomes Pinto de; Silva,Joaquim Augusto da; Sereno,Fabiana Tavares Pires de Souza; Mariante,Arthur da Silva

2007-01-01

Blood samples were collected from Pantaneiro Horses in five regions of Mato Grosso do Sul and Mato Grosso States. Arabian, Mangalarga Marchador and Thoroughbred were also included to estimate genetic distances and the existing variability among and within these breeds by RAPD-PCR (Random Amplified Polymorphic DNA - Polymerase Chain Reaction) molecular markers. From 146 primers, 13 were chosen for amplification and 44 polymorphic bands were generated. The analysis of molecular variance (AMOVA)...

Nonlinear Epigenetic Variance: Review and Simulations

Science.gov (United States)

Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.

2010-01-01

We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…

A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data

DEFF Research Database (Denmark)

Hansen, Peter Reinhard; Lunde, Asger

2005-01-01

We consider the problem of deriving an empirical measure of daily integrated variance (IV) in the situation where high-frequency price data are unavailable for part of the day. We study three estimators in this context and characterize the assumptions that justify their use. We show that the opti......We consider the problem of deriving an empirical measure of daily integrated variance (IV) in the situation where high-frequency price data are unavailable for part of the day. We study three estimators in this context and characterize the assumptions that justify their use. We show...

Revision: Variance Inflation in Regression

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D. R. Jensen

2013-01-01

the intercept; and (iv variance deflation may occur, where ill-conditioned data yield smaller variances than their orthogonal surrogates. Conventional VIFs have all regressors linked, or none, often untenable in practice. Beyond these, our models enable the unlinking of regressors that can be unlinked, while preserving dependence among those intrinsically linked. Moreover, known collinearity indices are extended to encompass angles between subspaces of regressors. To reaccess ill-conditioned data, we consider case studies ranging from elementary examples to data from the literature.

A new variance stabilizing transformation for gene expression data analysis.

Science.gov (United States)

Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor

2013-12-01

In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

Mean-Variance Analysis in a Multiperiod Setting

OpenAIRE

Frauendorfer, Karl; Siede, Heiko

1997-01-01

Similar to the classical Markowitz approach it is possible to apply a mean-variance criterion to a multiperiod setting to obtain efficient portfolios. To represent the stochastic dynamic characteristics necessary for modelling returns a process of asset returns is discretized with respect to time and space and summarized in a scenario tree. The resulting optimization problem is solved by means of stochastic multistage programming. The optimal solutions show equivalent structural properties as...

Computing the Expected Value and Variance of Geometric Measures

DEFF Research Database (Denmark)

Staals, Frank; Tsirogiannis, Constantinos

2017-01-01

distance (MPD), the squared Euclidean distance from the centroid, and the diameter of the minimum enclosing disk. We also describe an efficient (1-e)-approximation algorithm for computing the mean and variance of the mean pairwise distance. We implemented three of our algorithms and we show that our...

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

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Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

Variance estimation for generalized Cavalieri estimators

OpenAIRE

Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

2011-01-01

The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

Influence of Family Structure on Variance Decomposition

DEFF Research Database (Denmark)

Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter

Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

International Nuclear Information System (INIS)

Ankirchner, Stefan; Dermoune, Azzouz

2011-01-01

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

Energy Technology Data Exchange (ETDEWEB)

Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)

2011-08-15

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Hydrograph variances over different timescales in hydropower production networks

Science.gov (United States)

Zmijewski, Nicholas; Wörman, Anders

2016-08-01

The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of white noise) as a result of current production objectives.

Genetic Determinism and Evolutionary Reconstruction of a Host Jump in a Plant Virus.

Science.gov (United States)

Vassilakos, Nikon; Simon, Vincent; Tzima, Aliki; Johansen, Elisabeth; Moury, Benoît

2016-02-01

In spite of their widespread occurrence, only few host jumps by plant viruses have been evidenced and the molecular bases of even fewer have been determined. A combination of three independent approaches, 1) experimental evolution followed by reverse genetics analysis, 2) positive selection analysis, and 3) locus-by-locus analysis of molecular variance (AMOVA) allowed reconstructing the Potato virus Y (PVY; genus Potyvirus, family Potyviridae) jump to pepper (Capsicum annuum), probably from other solanaceous plants. Synthetic chimeras between infectious cDNA clones of two PVY isolates with contrasted levels of adaptation to C. annuum showed that the P3 and, to a lower extent, the CI cistron played important roles in infectivity toward C. annuum. The three analytical approaches pinpointed a single nonsynonymous substitution in the P3 and P3N-PIPO cistrons that evolved several times independently and conferred adaptation to C. annuum. In addition to increasing our knowledge of host jumps in plant viruses, this study illustrates also the efficiency of locus-by-locus AMOVA and combined approaches to identify adaptive mutations in the genome of RNA viruses. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Why risk is not variance: an expository note.

Science.gov (United States)

Cox, Louis Anthony Tony

2008-08-01

Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

Science.gov (United States)

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Variance bias analysis for the Gelbard's batch method

Energy Technology Data Exchange (ETDEWEB)

Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)

2014-05-15

In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.

A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

Science.gov (United States)

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

Response variance in functional maps: neural darwinism revisited.

Directory of Open Access Journals (Sweden)

Hirokazu Takahashi

Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response variance in functional maps: neural darwinism revisited.

Science.gov (United States)

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Integrating Variances into an Analytical Database

Science.gov (United States)

Sanchez, Carlos

2010-01-01

For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

Models of Postural Control: Shared Variance in Joint and COM Motions.

Directory of Open Access Journals (Sweden)

Melissa C Kilby

Full Text Available This paper investigated the organization of the postural control system in human upright stance. To this aim the shared variance between joint and 3D total body center of mass (COM motions was analyzed using multivariate canonical correlation analysis (CCA. The CCA was performed as a function of established models of postural control that varied in their joint degrees of freedom (DOF, namely, an inverted pendulum ankle model (2DOF, ankle-hip model (4DOF, ankle-knee-hip model (5DOF, and ankle-knee-hip-neck model (7DOF. Healthy young adults performed various postural tasks (two-leg and one-leg quiet stances, voluntary AP and ML sway on a foam and rigid surface of support. Based on CCA model selection procedures, the amount of shared variance between joint and 3D COM motions and the cross-loading patterns we provide direct evidence of the contribution of multi-DOF postural control mechanisms to human balance. The direct model fitting of CCA showed that incrementing the DOFs in the model through to 7DOF was associated with progressively enhanced shared variance with COM motion. In the 7DOF model, the first canonical function revealed more active involvement of all joints during more challenging one leg stances and dynamic posture tasks. Furthermore, the shared variance was enhanced during the dynamic posture conditions, consistent with a reduction of dimension. This set of outcomes shows directly the degeneracy of multivariate joint regulation in postural control that is influenced by stance and surface of support conditions.

Regional sensitivity analysis using revised mean and variance ratio functions

International Nuclear Information System (INIS)

Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen

2014-01-01

The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure

Variance risk premia in CO_2 markets: A political perspective

International Nuclear Information System (INIS)

Reckling, Dennis

2016-01-01

The European Commission discusses the change of free allocation plans to guarantee a stable market equilibrium. Selling over-allocated contracts effectively depreciates prices and negates the effect intended by the regulator to establish a stable price mechanism for CO_2 assets. Our paper investigates mispricing and allocation issues by quantitatively analyzing variance risk premia of CO_2 markets over the course of changing regimes (Phase I-III) for three different assets (European Union Allowances, Certified Emissions Reductions and European Reduction Units). The research paper gives recommendations to regulatory bodies in order to most effectively cap the overall carbon dioxide emissions. The analysis of an enriched dataset, comprising not only of additional CO_2 assets, but also containing data from the European Energy Exchange, shows that variance risk premia are equal to a sample average of 0.69 for European Union Allowances (EUA), 0.17 for Certified Emissions Reductions (CER) and 0.81 for European Reduction Units (ERU). We identify the existence of a common risk factor across different assets that justifies the presence of risk premia. Various policy implications with regards to gaining investors’ confidence in the market are being reviewed. Consequently, we recommend the implementation of a price collar approach to support stable prices for emission allowances. - Highlights: •Enriched dataset covering all three political phases of the CO_2 markets. •Clear policy implications for regulators to most effectively cap the overall CO_2 emissions pool. •Applying a cross-asset benchmark index for variance beta estimation. •CER contracts have been analyzed with respect to variance risk premia for the first time. •Increased forecasting accuracy for CO_2 asset returns by using variance risk premia.

The genotype-environment interaction variance in rice-seed protein determination

International Nuclear Information System (INIS)

Ismachin, M.

1976-01-01

Many environmental factors influence the protein content of cereal seed. This fact procured difficulties in breeding for protein. Yield is another example on which so many environmental factors are of influence. The length of time required by the plant to reach maturity, is also affected by the environmental factors; even though its effect is not too decisive. In this investigation the genotypic variance and the genotype-environment interaction variance which contribute to the total variance or phenotypic variance was analysed, with purpose to give an idea to the breeder how selection should be made. It was found that genotype-environment interaction variance is larger than the genotypic variance in contribution to total variance of protein-seed determination or yield. In the analysis of the time required to reach maturity it was found that genotypic variance is larger than the genotype-environment interaction variance. It is therefore clear, why selection for time required to reach maturity is much easier than selection for protein or yield. Selected protein in one location may be different from that to other locations. (author)

Estimation of measurement variances

International Nuclear Information System (INIS)

Jaech, J.L.

1984-01-01

The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

29 CFR 1905.5 - Effect of variances.

Science.gov (United States)

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

Realized range-based estimation of integrated variance

DEFF Research Database (Denmark)

Christensen, Kim; Podolskij, Mark

2007-01-01

We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...

Variance Function Partially Linear Single-Index Models1.

Science.gov (United States)

Lian, Heng; Liang, Hua; Carroll, Raymond J

2015-01-01

We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

Discrete time and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

Dominance genetic variance for traits under directional selection in Drosophila serrata.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.

Science.gov (United States)

Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S

2018-02-15

Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.

Analysis of force variance for a continuous miner drum using the Design of Experiments method

Energy Technology Data Exchange (ETDEWEB)

S. Somanchi; V.J. Kecojevic; C.J. Bise [Pennsylvania State University, University Park, PA (United States)

2006-06-15

Continuous miners (CMs) are excavating machines designed to extract a variety of minerals by underground mining. The variance in force experienced by the cutting drum is a very important aspect that must be considered during drum design. A uniform variance essentially means that an equal load is applied on the individual cutting bits and this, in turn, enables better cutting action, greater efficiency, and longer bit and machine life. There are certain input parameters used in the drum design whose exact relationships with force variance are not clearly understood. This paper determines (1) the factors that have a significant effect on the force variance of the drum and (2) the values that can be assigned to these factors to minimize the force variance. A computer program, Continuous Miner Drum (CMD), was developed in collaboration with Kennametal, Inc. to facilitate the mechanical design of CM drums. CMD also facilitated data collection for determining significant factors affecting force variance. Six input parameters, including centre pitch, outer pitch, balance angle, shift angle, set angle and relative angle were tested at two levels. Trials were configured using the Design of Experiments (DoE) method where 2{sup 6} full-factorial experimental design was selected to investigate the effect of these factors on force variance. Results from the analysis show that all parameters except balance angle, as well as their interactions, significantly affect the force variance.

Expected Stock Returns and Variance Risk Premia

DEFF Research Database (Denmark)

Bollerslev, Tim; Zhou, Hao

risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...

Measuring kinetics of complex single ion channel data using mean-variance histograms.

Science.gov (United States)

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance

Allowable variance set on left ventricular function parameter

International Nuclear Information System (INIS)

Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin

2010-01-01

Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)

Deviation of the Variances of Classical Estimators and Negative Integer Moment Estimator from Minimum Variance Bound with Reference to Maxwell Distribution

Directory of Open Access Journals (Sweden)

G. R. Pasha

2006-07-01

Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.

Numerical experiment on variance biases and Monte Carlo neutronics analysis with thermal hydraulic feedback

International Nuclear Information System (INIS)

Hyung, Jin Shim; Beom, Seok Han; Chang, Hyo Kim

2003-01-01

Monte Carlo (MC) power method based on the fixed number of fission sites at the beginning of each cycle is known to cause biases in the variances of the k-eigenvalue (keff) and the fission reaction rate estimates. Because of the biases, the apparent variances of keff and the fission reaction rate estimates from a single MC run tend to be smaller or larger than the real variances of the corresponding quantities, depending on the degree of the inter-generational correlation of the sample. We demonstrate this through a numerical experiment involving 100 independent MC runs for the neutronics analysis of a 17 x 17 fuel assembly of a pressurized water reactor (PWR). We also demonstrate through the numerical experiment that Gelbard and Prael's batch method and Ueki et al's covariance estimation method enable one to estimate the approximate real variances of keff and the fission reaction rate estimates from a single MC run. We then show that the use of the approximate real variances from the two-bias predicting methods instead of the apparent variances provides an efficient MC power iteration scheme that is required in the MC neutronics analysis of a real system to determine the pin power distribution consistent with the thermal hydraulic (TH) conditions of individual pins of the system. (authors)

Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study

International Nuclear Information System (INIS)

Zhai, Qingqing; Yang, Jun; Zhao, Yu

2014-01-01

Variance-based sensitivity analysis has been widely studied and asserted itself among practitioners. Monte Carlo simulation methods are well developed in the calculation of variance-based sensitivity indices but they do not make full use of each model run. Recently, several works mentioned a scatter-plot partitioning method to estimate the variance-based sensitivity indices from given data, where a single bunch of samples is sufficient to estimate all the sensitivity indices. This paper focuses on the space-partition method in the estimation of variance-based sensitivity indices, and its convergence and other performances are investigated. Since the method heavily depends on the partition scheme, the influence of the partition scheme is discussed and the optimal partition scheme is proposed based on the minimized estimator's variance. A decomposition and integration procedure is proposed to improve the estimation quality for higher order sensitivity indices. The proposed space-partition method is compared with the more traditional method and test cases show that it outperforms the traditional one

Time Consistent Strategies for Mean-Variance Asset-Liability Management Problems

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2013-01-01

Full Text Available This paper studies the optimal time consistent investment strategies in multiperiod asset-liability management problems under mean-variance criterion. By applying time consistent model of Chen et al. (2013 and employing dynamic programming technique, we derive two-time consistent policies for asset-liability management problems in a market with and without a riskless asset, respectively. We show that the presence of liability does affect the optimal strategy. More specifically, liability leads a parallel shift of optimal time-consistent investment policy. Moreover, for an arbitrarily risk averse investor (under the variance criterion with liability, the time-diversification effects could be ignored in a market with a riskless asset; however, it should be considered in a market without any riskless asset.

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.Th; Verburg, T.G.

2001-01-01

The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)

Some variance reduction methods for numerical stochastic homogenization.

Science.gov (United States)

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

variance components and genetic parameters for live weight

African Journals Online (AJOL)

admin

Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.

Restricted Variance Interaction Effects

DEFF Research Database (Denmark)

Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.

2018-01-01

Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...

Variance Swaps in BM&F: Pricing and Viability of Hedge

Directory of Open Access Journals (Sweden)

Richard John Brostowicz Junior

2010-07-01

Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.

Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study.

Science.gov (United States)

Kim, Minjung; Lamont, Andrea E; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M Lee

2016-06-01

Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.

Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.

Science.gov (United States)

Bright, Molly G; Murphy, Kevin

2015-07-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.

Integrating mean and variance heterogeneities to identify differentially expressed genes.

Science.gov (United States)

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1998-01-01

Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown

On the noise variance of a digital mammography system

International Nuclear Information System (INIS)

Burgess, Arthur

2004-01-01

A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel

Variance computations for functional of absolute risk estimates.

Science.gov (United States)

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

76 FR 78698 - Proposed Revocation of Permanent Variances

Science.gov (United States)

2011-12-19

... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...

Reduction of variance in spectral estimates for correction of ultrasonic aberration.

Science.gov (United States)

Astheimer, Jeffrey P; Pilkington, Wayne C; Waag, Robert C

2006-01-01

A variance reduction factor is defined to describe the rate of convergence and accuracy of spectra estimated from overlapping ultrasonic scattering volumes when the scattering is from a spatially uncorrelated medium. Assuming that the individual volumes are localized by a spherically symmetric Gaussian window and that centers of the volumes are located on orbits of an icosahedral rotation group, the factor is minimized by adjusting the weight and radius of each orbit. Conditions necessary for the application of the variance reduction method, particularly for statistical estimation of aberration, are examined. The smallest possible value of the factor is found by allowing an unlimited number of centers constrained only to be within a ball rather than on icosahedral orbits. Computations using orbits formed by icosahedral vertices, face centers, and edge midpoints with a constraint radius limited to a small multiple of the Gaussian width show that a significant reduction of variance can be achieved from a small number of centers in the confined volume and that this reduction is nearly the maximum obtainable from an unlimited number of centers in the same volume.

Diagnostic checking in linear processes with infinit variance

OpenAIRE

Krämer, Walter; Runde, Ralf

1998-01-01

We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.

MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE

Directory of Open Access Journals (Sweden)

I GEDE ERY NISCAHYANA

2016-08-01

Full Text Available When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK, Bank Permata Tbk (BNLI.JK, Suryamas Dutamakmur Tbk (SMDM.JK dan Semen Gresik Indonesia Tbk (SMGR.JK were estimated by GARCH(1,1 model with standard innovations following the standard normal distribution and the t-distribution.  The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94% of FMII stock, 0.0473 (5% of  BNLI stock, 0% of SMDM stock, 1% of  SMGR stock.

RR-Interval variance of electrocardiogram for atrial fibrillation detection

Science.gov (United States)

Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

2016-11-01

Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

OpenAIRE

Ma, Hui-qiang

2014-01-01

We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...

Variance based OFDM frame synchronization

Directory of Open Access Journals (Sweden)

Z. Fedra

2012-04-01

Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.

Enhancement of high-energy distribution tail in Monte Carlo semiconductor simulations using a Variance Reduction Scheme

Directory of Open Access Journals (Sweden)

Vincenza Di Stefano

2009-11-01

Full Text Available The Multicomb variance reduction technique has been introduced in the Direct Monte Carlo Simulation for submicrometric semiconductor devices. The method has been implemented in bulk silicon. The simulations show that the statistical variance of hot electrons is reduced with some computational cost. The method is efficient and easy to implement in existing device simulators.

Beyond the Mean: Sensitivities of the Variance of Population Growth.

Science.gov (United States)

Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad

2013-03-01

Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.

Evaluation of Mean and Variance Integrals without Integration

Science.gov (United States)

Joarder, A. H.; Omar, M. H.

2007-01-01

The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

Electron mobility variance in the presence of an electric field: Electron-phonon field-induced tunnel scattering

International Nuclear Information System (INIS)

Melkonyan, S.V.

2012-01-01

The problem of electron mobility variance is discussed. It is established that in equilibrium semiconductors the mobility variance is infinite. It is revealed that the cause of the mobility variance infinity is the threshold of phonon emission. The electron-phonon interaction theory in the presence of an electric field is developed. A new mechanism of electron scattering, called electron-phonon field-induced tunnel (FIT) scattering, is observed. The effect of the electron-phonon FIT scattering is explained in terms of penetration of the electron wave function into the semiconductor band gap in the presence of an electric field. New and more general expressions for the electron-non-polar optical phonon scattering probability and relaxation time are obtained. The results show that FIT transitions have principle meaning for the mobility fluctuation theory: mobility variance becomes finite.

Empirical single sample quantification of bias and variance in Q-ball imaging.

Science.gov (United States)

Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A

2018-02-06

The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.

Variance in binary stellar population synthesis

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2016-03-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

International Nuclear Information System (INIS)

Song Ningfang; Yuan Rui; Jin Jing

2011-01-01

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 0 /h 2 , K = 1.1714exp-3 0 /h 1.5 , B = 1.3185exp-3 0 /h, N = 5.982exp-4 0 /h 0.5 and Q = 5.197exp-7 0 in real time, and tracks degradation of gyro performance from initail values, R = 0.651 0 /h 2 , K = 0.801 0 /h 1.5 , B = 0.385 0 /h, N = 0.0874 0 /h 0.5 and Q = 8.085exp-5 0 , to final estimations, R = 9.548 0 /h 2 , K = 9.524 0 /h 1.5 , B = 2.234 0 /h, N = 0.5594 0 /h 0.5 and Q = 5.113exp-4 0 , due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

Argentine Population Genetic Structure: Large Variance in Amerindian Contribution

Science.gov (United States)

Seldin, Michael F.; Tian, Chao; Shigeta, Russell; Scherbarth, Hugo R.; Silva, Gabriel; Belmont, John W.; Kittles, Rick; Gamron, Susana; Allevi, Alberto; Palatnik, Simon A.; Alvarellos, Alejandro; Paira, Sergio; Caprarulo, Cesar; Guillerón, Carolina; Catoggio, Luis J.; Prigione, Cristina; Berbotto, Guillermo A.; García, Mercedes A.; Perandones, Carlos E.; Pons-Estel, Bernardo A.; Alarcon-Riquelme, Marta E.

2011-01-01

Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies. PMID:17177183

The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

Science.gov (United States)

Pressley, Joanna; Troyer, Todd W

2011-05-01

The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

Hidden temporal order unveiled in stock market volatility variance

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Y. Shapira

2011-06-01

Full Text Available When analyzed by standard statistical methods, the time series of the daily return of financial indices appear to behave as Markov random series with no apparent temporal order or memory. This empirical result seems to be counter intuitive since investor are influenced by both short and long term past market behaviors. Consequently much effort has been devoted to unveil hidden temporal order in the market dynamics. Here we show that temporal order is hidden in the series of the variance of the stocks volatility. First we show that the correlation between the variances of the daily returns and means of segments of these time series is very large and thus cannot be the output of random series, unless it has some temporal order in it. Next we show that while the temporal order does not show in the series of the daily return, rather in the variation of the corresponding volatility series. More specifically, we found that the behavior of the shuffled time series is equivalent to that of a random time series, while that of the original time series have large deviations from the expected random behavior, which is the result of temporal structure. We found the same generic behavior in 10 different stock markets from 7 different countries. We also present analysis of specially constructed sequences in order to better understand the origin of the observed temporal order in the market sequences. Each sequence was constructed from segments with equal number of elements taken from algebraic distributions of three different slopes.

Effect of sequence variants on variance in glucose levels predicts type 2 diabetes risk and accounts for heritability.

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Ivarsdottir, Erna V; Steinthorsdottir, Valgerdur; Daneshpour, Maryam S; Thorleifsson, Gudmar; Sulem, Patrick; Holm, Hilma; Sigurdsson, Snaevar; Hreidarsson, Astradur B; Sigurdsson, Gunnar; Bjarnason, Ragnar; Thorsson, Arni V; Benediktsson, Rafn; Eyjolfsson, Gudmundur; Sigurdardottir, Olof; Olafsson, Isleifur; Zeinali, Sirous; Azizi, Fereidoun; Thorsteinsdottir, Unnur; Gudbjartsson, Daniel F; Stefansson, Kari

2017-09-01

Sequence variants that affect mean fasting glucose levels do not necessarily affect risk for type 2 diabetes (T2D). We assessed the effects of 36 reported glucose-associated sequence variants on between- and within-subject variance in fasting glucose levels in 69,142 Icelanders. The variant in TCF7L2 that increases fasting glucose levels increases between-subject variance (5.7% per allele, P = 4.2 × 10 -10 ), whereas variants in GCK and G6PC2 that increase fasting glucose levels decrease between-subject variance (7.5% per allele, P = 4.9 × 10 -11 and 7.3% per allele, P = 7.5 × 10 -18 , respectively). Variants that increase mean and between-subject variance in fasting glucose levels tend to increase T2D risk, whereas those that increase the mean but reduce variance do not (r 2 = 0.61). The variants that increase between-subject variance increase fasting glucose heritability estimates. Intuitively, our results show that increasing the mean and variance of glucose levels is more likely to cause pathologically high glucose levels than increase in the mean offset by a decrease in variance.

Reduced Variance of Gene Expression at Numerous Loci in a Population of Chickens Selected for High Feather Pecking

DEFF Research Database (Denmark)

Hughes, A L; Buitenhuis, A J

2010-01-01

among populations with respect to mean expression scores, but numerous transcripts showed reduced variance in expression scores in the high FP population in comparison to control and low FP populations. The reduction in variance in the high FP population generally involved transcripts whose expression...

Relative variance of the mean-squared pressure in multimode media: rehabilitating former approaches.

Science.gov (United States)

Monsef, Florian; Cozza, Andrea; Rodrigues, Dominique; Cellard, Patrick; Durocher, Jean-Noel

2014-11-01

The commonly accepted model for the relative variance of transmission functions in room acoustics, derived by Weaver, aims at including the effects of correlation between eigenfrequencies. This model is based on an analytical expression of the relative variance derived by means of an approximated correlation function. The relevance of the approximation used for modeling such correlation is questioned here. Weaver's model was motivated by the fact that earlier models derived by Davy and Lyon assumed independent eigenfrequencies and led to an overestimation with respect to relative variances found in practice. It is shown here that this overestimation is due to an inadequate truncation of the modal expansion, and to an improper choice of the frequency range over which ensemble averages of the eigenfrequencies is defined. An alternative definition is proposed, settling the inconsistency; predicted relative variances are found to be in good agreement with experimental data. These results rehabilitate former approaches that were based on independence assumptions between eigenfrequencies. Some former studies showed that simpler correlation models could be used to predict the statistics of some field-related physical quantity at low modal overlap. The present work confirms that this is also the case when dealing with transmission functions.

Is fMRI “noise” really noise? Resting state nuisance regressors remove variance with network structure

Science.gov (United States)

Bright, Molly G.; Murphy, Kevin

2015-01-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured “signal” as well as “noise.” Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. PMID:25862264

Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

DEFF Research Database (Denmark)

Christoffersen, Peter; Heston, Steven; Jacobs, Kris

2013-01-01

We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....

Gender Variance and Educational Psychology: Implications for Practice

Science.gov (United States)

Yavuz, Carrie

2016-01-01

The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

Epidemic dynamics of two coexisting hepatitis C virus subtypes.

Science.gov (United States)

Jiménez-Hernández, Nuria; Torres-Puente, Manuela; Bracho, Maria Alma; García-Robles, Inmaculada; Ortega, Enrique; del Olmo, Juan; Carnicer, Fernando; González-Candelas, Fernando; Moya, Andrés

2007-01-01

Hepatitis C virus (HCV) infection affects about 3% of the human population. Phylogenetic analyses have grouped its variants into six major genotypes, which have a star-like distribution and several minor subtypes. The most abundant genotype in Europe is the so-called genotype 1, with two prevalent subtypes, 1a and 1b. In order to explain the higher prevalence of subtype 1b over 1a, a large-scale sequence analysis (100 virus clones) has been carried out over 25 patients of both subtypes in two regions of the HCV genome: one comprising hypervariable region 1 and another including the interferon sensitivity-determining region. Neither polymorphism analysis nor molecular variance analysis (attending to intra- and intersubtype differences, age, sex and previous history of antiviral treatment) was able to show any particular difference between subtypes that might account for their different prevalence. Only the demographic history of the populations carrying both subtypes and analysis of molecular variance (AMOVA) for risk practice suggested that the route of transmission may be the most important factor to explain the observed difference.

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)

2011-07-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

Variance-in-Mean Effects of the Long Forward-Rate Slope

DEFF Research Database (Denmark)

Christiansen, Charlotte

2005-01-01

This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....

Non-Linear Transaction Costs Inclusion in Mean-Variance Optimization

Directory of Open Access Journals (Sweden)

Christian Johannes Zimmer

2005-12-01

Full Text Available In this article we propose a new way to include transaction costs into a mean-variance portfolio optimization. We consider brokerage fees, bid/ask spread and the market impact of the trade. A pragmatic algorithm is proposed, which approximates the optimal portfolio, and we can show that is converges in the absence of restrictions. Using Brazilian financial market data we compare our approximation algorithm with the results of a non-linear optimizer.

Tests and Confidence Intervals for an Extended Variance Component Using the Modified Likelihood Ratio Statistic

DEFF Research Database (Denmark)

Christensen, Ole Fredslund; Frydenberg, Morten; Jensen, Jens Ledet

2005-01-01

The large deviation modified likelihood ratio statistic is studied for testing a variance component equal to a specified value. Formulas are presented in the general balanced case, whereas in the unbalanced case only the one-way random effects model is studied. Simulation studies are presented......, showing that the normal approximation to the large deviation modified likelihood ratio statistic gives confidence intervals for variance components with coverage probabilities very close to the nominal confidence coefficient....

Complementary responses to mean and variance modulations in the perfect integrate-and-fire model.

Science.gov (United States)

Pressley, Joanna; Troyer, Todd W

2009-07-01

In the perfect integrate-and-fire model (PIF), the membrane voltage is proportional to the integral of the input current since the time of the previous spike. It has been shown that the firing rate within a noise free ensemble of PIF neurons responds instantaneously to dynamic changes in the input current, whereas in the presence of white noise, model neurons preferentially pass low frequency modulations of the mean current. Here, we prove that when the input variance is perturbed while holding the mean current constant, the PIF responds preferentially to high frequency modulations. Moreover, the linear filters for mean and variance modulations are complementary, adding exactly to one. Since changes in the rate of Poisson distributed inputs lead to proportional changes in the mean and variance, these results imply that an ensemble of PIF neurons transmits a perfect replica of the time-varying input rate for Poisson distributed input. A more general argument shows that this property holds for any signal leading to proportional changes in the mean and variance of the input current.

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1997-08-01

Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

Science.gov (United States)

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination

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Liangping Wu

2014-08-01

Full Text Available Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.

Variance swap payoffs, risk premia and extreme market conditions

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco

This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....

The Pricing of European Options Under the Constant Elasticity of Variance with Stochastic Volatility

Science.gov (United States)

Bock, Bounghun; Choi, Sun-Yong; Kim, Jeong-Hoon

This paper considers a hybrid risky asset price model given by a constant elasticity of variance multiplied by a stochastic volatility factor. A multiscale analysis leads to an asymptotic pricing formula for both European vanilla option and a Barrier option near the zero elasticity of variance. The accuracy of the approximation is provided in a rigorous manner. A numerical experiment for implied volatilities shows that the hybrid model improves some of the well-known models in view of fitting the data for different maturities.

Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability

DEFF Research Database (Denmark)

Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco

We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....

A note on minimum-variance theory and beyond

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)

2004-04-30

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.

A note on minimum-variance theory and beyond

International Nuclear Information System (INIS)

Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello

2004-01-01

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons

Estimation of Anadara tuberculosa genetic diversity in five mangroves from Tumaco, using Cytochrome oxidase I enzyme

Directory of Open Access Journals (Sweden)

Esmeralda Chamorro L

2016-09-01

Full Text Available Objective. To estimate the genetic diversity of the Anadara tuberculosa en five mangrove swams of Tumaco, Nariño, Colombia using as a mitocondrial molecular marker the cytochromo oxidase sub-unit I (COI. Materials and methods. A total of 50 individuals were collected from the San Jorge, La Tiburonera, El Pajal, La Playa y Bajito Vaquería mangrove swamps, randomly selecting 10 specimens of each zone. The tissue sample was worked with absolute alcohol at ambient temperature in microtubes. DNA was extracted, and the mitocondrial DNA was amplified using the PCR technique (polymerase chain reaction. The amplified and quantified products of PCR were sequenced on both sides (Macrogen. Each one of the obtained sequences was edited and aligned. Later, the parameters of genetic diversity (haplotypical and nucleotidical were measured, and the analysis of distribution between frequency pairs (Mistmach distribution was elaborated. Finally, the analysis of nucleotidic variation and population structure (AMOVA was completed. Results. The amplified product gene weighed 710 bp. The haplotypical diversity reported for all the populations was high (0.683±0.060 and the reported nucleotídical diversity was low for all the populations (0.040±0.020. The AMOVA results indicate that the variance amongst populations is low (4.20% and that the variance within populations is high (95.80%. Conclusions. The studied populations are not structured and although there is a decrease of natural banks, the genetic diversity is high.

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat

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Abdulqader Jighly

2018-02-01

Full Text Available Whole genome duplication (WGD is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome. The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy

Flow rate dependent extra-column variance from injection in capillary liquid chromatography.

Science.gov (United States)

Aggarwal, Pankaj; Liu, Kun; Sharma, Sonika; Lawson, John S; Dennis Tolley, H; Lee, Milton L

2015-02-06

Efficiency and resolution in capillary liquid chromatography (LC) can be significantly affected by extra-column band broadening, especially for isocratic separations. This is particularly a concern in evaluating column bed structure using non-retained test compounds. The band broadening due to an injector supplied with a commercially available capillary LC system was characterized from experimental measurements. The extra-column variance from the injection valve was found to have an extra-column contribution independent of the injection volume, showing an exponential dependence on flow rate. The overall extra-column variance from the injection valve was found to vary from 34 to 23 nL. A new mathematical model was derived that explains this exponential contribution of extra-column variance on chromatographic performance. The chromatographic efficiency was compromised by ∼130% for a non-retained analyte because of injection valve dead volume. The measured chromatographic efficiency was greatly improved when a new nano-flow pumping system with integrated injection valve was used. Copyright © 2014 Elsevier B.V. All rights reserved.

Conservation genetics of the critically endangered Round Island bottle palm, Hyophorbe lagenicaulis (Arecaceae)

DEFF Research Database (Denmark)

Lange, Conny Bruun Asmussen; Maunder, Michael; Fay, Michael F.

2011-01-01

The amplified fragment length polymorphism (AFLP) technique was used to examine genetic variation among old and newly emerged individuals of Hyophorbe lagenicaulis (the Round Island bottle palm) on Round Island to assess surviving levels of diversity in the wild population and to evaluate...... monomorphic bands. Analysis of molecular variance (AMOVA) and Shannon’s indices showed a high level of genetic variation within the wild population on Round Island and a smaller amount of genetic variation among cultivated individuals. A neighbor joining analysis resulted in an unrooted network of genetic...... distances in which the five Hyophorbe spp. were separated and much variation within H. lagenicaulis was recovered. The Round Island populations of H. lagenicaulis contain representatives of the genetic variation found within the species as a whole. However, a few individuals, both wild and cultivated...

Identification of melanoma cells: a method based in mean variance of signatures via spectral densities.

Science.gov (United States)

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué; Angulo-Molina, Aracely

2017-04-01

In this paper a new methodology to detect and differentiate melanoma cells from normal cells through 1D-signatures averaged variances calculated with a binary mask is presented. The sample images were obtained from histological sections of mice melanoma tumor of 4 [Formula: see text] in thickness and contrasted with normal cells. The results show that melanoma cells present a well-defined range of averaged variances values obtained from the signatures in the four conditions used.

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

International Nuclear Information System (INIS)

Christoforou, Stavros; Hoogenboom, J. Eduard

2011-01-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

Structural changes and out-of-sample prediction of realized range-based variance in the stock market

Science.gov (United States)

Gong, Xu; Lin, Boqiang

2018-03-01

This paper aims to examine the effects of structural changes on forecasting the realized range-based variance in the stock market. Considering structural changes in variance in the stock market, we develop the HAR-RRV-SC model on the basis of the HAR-RRV model. Subsequently, the HAR-RRV and HAR-RRV-SC models are used to forecast the realized range-based variance of S&P 500 Index. We find that there are many structural changes in variance in the U.S. stock market, and the period after the financial crisis contains more structural change points than the period before the financial crisis. The out-of-sample results show that the HAR-RRV-SC model significantly outperforms the HAR-BV model when they are employed to forecast the 1-day, 1-week, and 1-month realized range-based variances, which means that structural changes can improve out-of-sample prediction of realized range-based variance. The out-of-sample results remain robust across the alternative rolling fixed-window, the alternative threshold value in ICSS algorithm, and the alternative benchmark models. More importantly, we believe that considering structural changes can help improve the out-of-sample performances of most of other existing HAR-RRV-type models in addition to the models used in this paper.

Variance stabilization for computing and comparing grand mean waveforms in MEG and EEG.

Science.gov (United States)

Matysiak, Artur; Kordecki, Wojciech; Sielużycki, Cezary; Zacharias, Norman; Heil, Peter; König, Reinhard

2013-07-01

Grand means of time-varying signals (waveforms) across subjects in magnetoencephalography (MEG) and electroencephalography (EEG) are commonly computed as arithmetic averages and compared between conditions, for example, by subtraction. However, the prerequisite for these operations, homogeneity of the variance of the waveforms in time, and for most common parametric statistical tests also between conditions, is rarely met. We suggest that the heteroscedasticity observed instead results because waveforms may differ by factors and additive terms and follow a mixed model. We propose to apply the asinh-transformation to stabilize the variance in such cases. We demonstrate the homogeneous variance and the normal distributions of data achieved by this transformation using simulated waveforms, and we apply it to real MEG data and show its benefits. The asinh-transformation is thus an essential and useful processing step prior to computing and comparing grand mean waveforms in MEG and EEG. Copyright © 2013 Society for Psychophysiological Research.

Evaluation of genetic diversity of Panicum turgidum Forssk from Saudi Arabia.

Science.gov (United States)

Assaeed, Abdulaziz M; Al-Faifi, Sulieman A; Migdadi, Hussein M; El-Bana, Magdy I; Al Qarawi, Abdulaziz A; Khan, Mohammad Altaf

2018-01-01

The genetic diversity of 177 accessions of Panicum turgidum Forssk, representing ten populations collected from four geographical regions in Saudi Arabia, was analyzed using amplified fragment length polymorphism (AFLP) markers. A set of four primer-pairs with two/three selective nucleotides scored 836 AFLP amplified fragments (putative loci/genome landmarks), all of which were polymorphic. Populations collected from the southern region of the country showed the highest genetic diversity parameters, whereas those collected from the central regions showed the lowest values. Analysis of molecular variance (AMOVA) revealed that 78% of the genetic variability was attributable to differences within populations. Pairwise values for population differentiation and genetic structure were statistically significant for all variances. The UPGMA dendrogram, validated by principal coordinate analysis-grouped accessions, corresponded to the geographical origin of the accessions. Mantel's test showed that there was a significant correlation between the genetic and geographical distances ( r  = 0.35, P  < 0.04). In summary, the AFLP assay demonstrated the existence of substantial genetic variation in P. turgidum . The relationship between the genetic diversity and geographical source of P. turgidum populations of Saudi Arabia, as revealed through this comprehensive study, will enable effective resource management and restoration of new areas without compromising adaptation and genetic diversity.

Minimal sharing of Y-chromosome STR haplotypes among five endogamous population groups from western and southwestern India.

Science.gov (United States)

Das, Birajalaxmi; Chauhan, P S; Seshadri, M

2004-10-01

We attempt to address the issue of genetic variation and the pattern of male gene flow among and between five Indian population groups of two different geographic and linguistic affiliations using Y-chromosome markers. We studied 221 males at three Y-chromosome biallelic loci and 184 males for the five Y-chromosome STRs. We observed 111 Y-chromosome STR haplotypes. An analysis of molecular variance (AMOVA) based on Y-chromosome STRs showed that the variation observed between the population groups belonging to two major regions (western and southwestern India) was 0.17%, which was significantly lower than the level of genetic variance among the five populations (0.59%) considered as a single group. Combined haplotype analysis of the five STRs and the biallelic locus 92R7 revealed minimal sharing of haplotypes among these five ethnic groups, irrespective of the similar origin of the linguistic and geographic affiliations; this minimal sharing indicates restricted male gene flow. As a consequence, most of the haplotypes were population specific. Network analysis showed that the haplotypes, which were shared between the populations, seem to have originated from different mutational pathways at different loci. Biallelic markers showed that all five ethnic groups have a similar ancestral origin despite their geographic and linguistic diversity.

SCoT marker for the assessment of genetic diversity in saudi arabian date palm cultivars

International Nuclear Information System (INIS)

Qurainy, F.A.; Tarroum, M.

2015-01-01

Different types of molecular markers based on DNA have been used for the assessment of genetic diversity in the plant species. Start Codon Targeted Polymorphism (SCoT) marker has recently become the marker of choice in genetic diversity studies. SCoT marker was used for the assessment of genetic diversity in Saudi Arabian date palm cultivars. The percentage of polymorphic loci (PPL) at population level ranged from 3.28 to 13.11 with an average of 7.10. The Neis gene diversity (h) and Shannons Information index (I) were 0.033 and 0.046, respectively. However, at cultivar level, PPL, Neis gene diversity (h) and Shannons Information index (I) were 42.62, 0.090 and 0.155, respectively. Analysis of molecular variance (AMOVA) showed 48% of variation within the populations, whereas 52% was found among the populations. A hierarchical analysis of molecular variance revealed level of genetic differentiation among populations (52% of total variance, P = 0.001), consistent with the gene differentiation coefficient (Gst = 0.631). Unweighted pair group method of arithmetic averages (UPGMA) cluster analysis of the SCoT marker data divided the six cultivars and their populations into five main clusters at 0.95 genetic similarity coefficient level. (author)

The mean–variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI

Science.gov (United States)

Thompson, William H.; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed. PMID:26236216

Adding a Parameter Increases the Variance of an Estimated Regression Function

Science.gov (United States)

Withers, Christopher S.; Nadarajah, Saralees

2011-01-01

The linear regression model is one of the most popular models in statistics. It is also one of the simplest models in statistics. It has received applications in almost every area of science, engineering and medicine. In this article, the authors show that adding a predictor to a linear model increases the variance of the estimated regression…

On Mean-Variance Analysis

OpenAIRE

Li, Yang; Pirvu, Traian A

2011-01-01

This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.

Analysis of rhythmic variance - ANORVA. A new simple method for detecting rhythms in biological time series

Directory of Open Access Journals (Sweden)

Peter Celec

2004-01-01

Full Text Available Cyclic variations of variables are ubiquitous in biomedical science. A number of methods for detecting rhythms have been developed, but they are often difficult to interpret. A simple procedure for detecting cyclic variations in biological time series and quantification of their probability is presented here. Analysis of rhythmic variance (ANORVA is based on the premise that the variance in groups of data from rhythmic variables is low when a time distance of one period exists between the data entries. A detailed stepwise calculation is presented including data entry and preparation, variance calculating, and difference testing. An example for the application of the procedure is provided, and a real dataset of the number of papers published per day in January 2003 using selected keywords is compared to randomized datasets. Randomized datasets show no cyclic variations. The number of papers published daily, however, shows a clear and significant (p<0.03 circaseptan (period of 7 days rhythm, probably of social origin

Modelling volatility by variance decomposition

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

Science.gov (United States)

DeCarlo, Lawrence T

2003-02-01

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

Phylogeography of the dark fruit-eating bat Artibeus obscurus in the Brazilian Amazon.

Science.gov (United States)

Ferreira, Wallax Augusto Silva; Borges, Bárbara do Nascimento; Rodrigues-Antunes, Symara; de Andrade, Fernanda Atanaena Gonçalves; Aguiar, Gilberto Ferreira de Souza; de Sousa e Silva-Junior, José; Marques-Aguiar, Suely Aparecida; Harada, Maria Lúcia

2014-01-01

Artibeus obscurus (Mammalia: Chiroptera) is endemic to South America, being found in at least 18 Brazilian states. Recent studies revealed that different populations of this genus present distinct phylogeographic patterns; however, very little is known on the population genetics structure of A. obscurus in the Amazon rainforest. Here, using a fragment (1010bp) of the mitochondrial gene cytochrome b from 87 samples, we investigated patterns of genetic divergence among populations of A. obscurus from different locations in the Brazilian Amazon rainforest and compared them with other Brazilian and South American regions. Analysis of molecular variance (AMOVA), fixation index (Fst) analysis, and phylogeographic patterns showed divergence between two major monophyletic groups, each one corresponding to a geographic region associated with the Atlantic and Amazon forest biomes. The Atlantic forest clusters formed a monophyletic group with a high bootstrap support and a fragmented distribution that follows the pattern predicted by the Refuge Theory. On the other hand, a different scenario was observed for the Amazon forest, where no fragmentation was identified. The AMOVA results revealed a significant geographic heterogeneity in the distribution of genetic variation, with 70% found within populations across the studied populations (Fst values ranging from 0.05864 to 0.09673; φST = 0.55). The intrapopulational analysis revealed that one population (Bragança) showed significant evidence of population expansion, with the formation of 2 distinct phylogroups, suggesting the occurrence of a subspecies or at least a different population in this region. These results also suggest considerable heterogeneity for A. obscurus in the Amazon region.

Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

Science.gov (United States)

Zapko-Willmes, Alexandra; Kandler, Christian

2018-01-01

The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

Decomposition of Variance for Spatial Cox Processes.

Science.gov (United States)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-03-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

Energy Technology Data Exchange (ETDEWEB)

Song Ningfang; Yuan Rui; Jin Jing, E-mail: rayleing@139.com [School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191 (China)

2011-09-15

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 {sup 0}/h{sup 2}, K = 1.1714exp-3 {sup 0}/h{sup 1.5}, B = 1.3185exp-3 {sup 0}/h, N = 5.982exp-4 {sup 0}/h{sup 0.5} and Q = 5.197exp-7 {sup 0} in real time, and tracks degradation of gyro performance from initail values, R = 0.651 {sup 0}/h{sup 2}, K = 0.801 {sup 0}/h{sup 1.5}, B = 0.385 {sup 0}/h, N = 0.0874 {sup 0}/h{sup 0.5} and Q = 8.085exp-5 {sup 0}, to final estimations, R = 9.548 {sup 0}/h{sup 2}, K = 9.524 {sup 0}/h{sup 1.5}, B = 2.234 {sup 0}/h, N = 0.5594 {sup 0}/h{sup 0.5} and Q = 5.113exp-4 {sup 0}, due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

Grammatical and lexical variance in English

CERN Document Server

Quirk, Randolph

2014-01-01

Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.

The contribution of the mitochondrial genome to sex-specific fitness variance.

Science.gov (United States)

Smith, Shane R T; Connallon, Tim

2017-05-01

Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance-based Salt Body Reconstruction

KAUST Repository

Ovcharenko, Oleg

2017-05-26

Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

Science.gov (United States)

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Minimum variance Monte Carlo importance sampling with parametric dependence

International Nuclear Information System (INIS)

Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

1981-01-01

An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

Exploring variance in residential electricity consumption: Household features and building properties

International Nuclear Information System (INIS)

Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars

2012-01-01

Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.

Discussion on variance reduction technique for shielding

Energy Technology Data Exchange (ETDEWEB)

Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-03-01

As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)

Capturing option anomalies with a variance-dependent pricing kernel

NARCIS (Netherlands)

Christoffersen, P.; Heston, S.; Jacobs, K.

2013-01-01

We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

29 CFR 1904.38 - Variances from the recordkeeping rule.

Science.gov (United States)

2010-07-01

..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...

The Efficiency of Split Panel Designs in an Analysis of Variance Model

Science.gov (United States)

Wang, Wei-Guo; Liu, Hai-Jun

2016-01-01

We consider split panel design efficiency in analysis of variance models, that is, the determination of the cross-sections series optimal proportion in all samples, to minimize parametric best linear unbiased estimators of linear combination variances. An orthogonal matrix is constructed to obtain manageable expression of variances. On this basis, we derive a theorem for analyzing split panel design efficiency irrespective of interest and budget parameters. Additionally, relative estimator efficiency based on the split panel to an estimator based on a pure panel or a pure cross-section is present. The analysis shows that the gains from split panel can be quite substantial. We further consider the efficiency of split panel design, given a budget, and transform it to a constrained nonlinear integer programming. Specifically, an efficient algorithm is designed to solve the constrained nonlinear integer programming. Moreover, we combine one at time designs and factorial designs to illustrate the algorithm’s efficiency with an empirical example concerning monthly consumer expenditure on food in 1985, in the Netherlands, and the efficient ranges of the algorithm parameters are given to ensure a good solution. PMID:27163447

Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.

Science.gov (United States)

Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J

2015-01-01

Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.

Decomposition of variance in terms of conditional means

Directory of Open Access Journals (Sweden)

Alessandro Figà Talamanca

2013-05-01

Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..

42 CFR 456.522 - Content of request for variance.

Science.gov (United States)

2010-10-01

... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...

On the Endogeneity of the Mean-Variance Efficient Frontier.

Science.gov (United States)

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Assessment of ulnar variance: a radiological investigation in a Dutch population

Energy Technology Data Exchange (ETDEWEB)

Schuurman, A.H. [Dept. of Plastic, Reconstructive and Hand Surgery, University Medical Centre, Utrecht (Netherlands); Dept. of Plastic Surgery, University Medical Centre, Utrecht (Netherlands); Maas, M.; Dijkstra, P.F. [Dept. of Radiology, Univ. of Amsterdam (Netherlands); Kauer, J.M.G. [Dept. of Anatomy and Embryology, Univ. of Nijmegen (Netherlands)

2001-11-01

Objective: A radiological study was performed to evaluate ulnar variance in 68 Dutch patients using an electronic digitizer compared with Palmer's concentric circle method. Using the digitizer method only, the effect of different wrist positions and grip on ulnar variance was then investigated. Finally the distribution of ulnar variance in the selected patients was investigated also using the digitizer method. Design and patients: All radiographs were performed with the wrist in a standard zero-rotation position (posteroanterior) and in supination (anteroposterior). Palmer's concentric circle method and an electronic digitizer connected to a personal computer were used to measure ulnar variance. The digitizer consists of a Plexiglas plate with an electronically activated grid beneath it. A radiograph is placed on the plate and a cursor activates a point on the grid. Three plots are marked on the radius and one plot on the most distal part of the ulnar head. The digitizer then determines the difference between a radius passing through the radius plots and the ulnar plot. Results and conclusions: Using the concentric circle method we found an ulna plus predominance, but an ulna minus predominance when using the digitizer method. Overall the ulnar variance distribution for Palmer's method was 41.9% ulna plus, 25.7% neutral and 32.4% ulna minus variance, and for the digitizer method was 40.4% ulna plus, 1.5% neutral and 58.1% ulna minus. The percentage ulnar variance greater than 1 mm on standard radiographs increased from 23% to 58% using the digitizer, with maximum grip, clearly demonstrating the (dynamic) effect of grip on ulnar variance. This almost threefold increase was found to be a significant difference. Significant differences were found between ulnar variance when different wrist positions were compared. (orig.)

Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-07-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

A versatile omnibus test for detecting mean and variance heterogeneity.

Science.gov (United States)

Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.

Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-01-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

Global Variance Risk Premium and Forex Return Predictability

OpenAIRE

Aloosh, Arash

2014-01-01

In a long-run risk model with stochastic volatility and frictionless markets, I express expected forex returns as a function of consumption growth variances and stock variance risk premiums (VRPs)—the difference between the risk-neutral and statistical expectations of market return variation. This provides a motivation for using the forward-looking information available in stock market volatility indices to predict forex returns. Empirically, I find that stock VRPs predict forex returns at a ...

Variance components for body weight in Japanese quails (Coturnix japonica

Directory of Open Access Journals (Sweden)

RO Resende

2005-03-01

Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.

Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

DEFF Research Database (Denmark)

Ashraf, Bilal; Janss, Luc; Jensen, Just

sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...

29 CFR 1920.2 - Variances.

Science.gov (United States)

2010-07-01

...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

Zero-intelligence realized variance estimation

NARCIS (Netherlands)

Gatheral, J.; Oomen, R.C.A.

2010-01-01

Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and

Genetic admixture estimates by Alu elements in Afro-Colombian and Mestizo populations from Antioquia, Colombia.

Science.gov (United States)

Gómez-Pérez, Luis; Alfonso-Sánchez, Miguel A; Pérez-Miranda, Ana M; García-Obregón, Susana; Builes, Juan J; Bravo, Maria L; De Pancorbo, Marian M; Peña, José A

2010-08-01

This work was intended to gain insights into the admixture processes occurring in Latin American populations by examining the genetic profiles of two ethnic groups from Antioquia (Colombia). To analyse the genetic variability, eight Alu insertions were typed in 64 Afro-Colombians and a reference group of 34 Hispanics (Mestizos). Admixture proportions were estimated using the Weighted Least Squares and the Gene Identity methods. The usefulness of the Alu elements as Ancestry Informative Markers (AIMs) was evaluated through differences in weighted allelic frequencies (delta values) and by hierarchical analysis of the molecular variance (AMOVA). The Afro-Colombian gene pool was largely determined by the African component (88.5-88.8%), but the most prominent feature was the null contribution of European genes. Mestizos were characterized by a major European component (60.0-63.8%) and a comparatively low proportion of Amerindian (19.2-20.7%) and African (17.0-19.3%) genes. Five of the Alu loci examined (ACE, APO, FXIIIB, PV92 and TPA25) showed an adequate resolving power to differentiate between continental groups, as indicated by delta values and AMOVA results. The peculiarity of the Afro-Colombian gene pool seems to be associated with intense genetic drift episodes that occurred in isolated communities founded by small groups of runaway slaves. ACE, APO, FXIIIB, PV92 and TPA25 could be efficiently utilized in studies dealing with demographic history and biogeographical ancestry in human populations.

Population Genetic Structure and Evidence of Demographic Expansion of the Ayu (Plecoglossus altivelis in East Asia

Directory of Open Access Journals (Sweden)

Ye-Seul Kwan

2012-10-01

Full Text Available Plecoglossus altivelis (ayu is an amphidromous fish widely distributed in Northeastern Asia from the East China Sea to the northern Japanese coastal waters, encompassing the Korean Peninsula within its range. The shore lines of northeastern region in Asia have severely fluctuated following glaciations in the Quaternary. In the present study, we investigate the population genetic structure and historical demographic change of P. altivelis at a population level in East Asia. Analysis of molecular variance (AMOVA based on 244 mitochondrial control region DNA sequences clearly showed that as the sampling scope extended to a larger geographic area, genetic differentiation began to become significant, particularly among Northeastern populations. A series of hierarchical AMOVA could detect the genetic relationship of three closely located islands between Korea and Japan that might have been tightly connected by the regional Tsushima current. Neutrality and mismatch distribution analyses revealed a strong signature of a recent population expansion of P. altivelis in East Asia, estimated at 126 to 391 thousand years ago during the late Pleistocene. Therefore it suggests that the present population of P. altivelis traces back to its approximate demographic change long before the last glacial maximum. This contrasts our a priori expectation that the most recent glacial event might have the most crucial effect on the present day demography of marine organisms through bottleneck and subsequent increase of effective population size in this region.

Patterns of genetic diversity of local pig populations in the State of Pernambuco, Brazil

Directory of Open Access Journals (Sweden)

Elizabete Cristina da Silva

2011-08-01

Full Text Available This study estimated the genetic diversity and structure of 12 genetic groups (GG of locally adapted and specialized pigs in the state of Pernambuco using 22 microsatellite markers. Nine locally adapted breeds (Baé, Caruncho, Canastra, Canastrão, Mamelado, Moura, Nilo, Piau and UDB (Undefined Breed and 3 specialized breeds (Duroc, Landrace and Large White, totaling 190 animals, were analyzed. The Analysis of Molecular Variance (AMOVA showed that 3.2% of the total variation was due to differences between genetic groups, and 3.6% to differences between local and commercial pigs. One hundred and ninety eight alleles were identified and apart from the Large White breed, all GG presented Hardy-Weinberg Equilibrium deviations for some loci. The total and effective allele means were lower for Duroc (3.65 and 3.01 and higher for UDB (8.89 and 4.53 and Canastra (8.61 and 4.58. Using Nei's standard genetic distance and the UPGMA method, it was possible to observe that the Landrace breed was grouped with the local genetic groups Canastra, Moura, Canastrão, Baé and Caruncho. Due to the complex admixture pattern, the genetic variability of the 12 genetic groups can be analyzed by distributing the individuals into two populations as demonstrated by a Bayesian analysis, corroborating the results from AMOVA, which revealed a low level of genetic differentiation between the inferred populations.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

On robust multi-period pre-commitment and time-consistent mean-variance portfolio optimization

NARCIS (Netherlands)

F. Cong (Fei); C.W. Oosterlee (Kees)

2017-01-01

textabstractWe consider robust pre-commitment and time-consistent mean-variance optimal asset allocation strategies, that are required to perform well also in a worst-case scenario regarding the development of the asset price. We show that worst-case scenarios for both strategies can be found by

Phenotypic variance explained by local ancestry in admixed African Americans.

Science.gov (United States)

Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N

2015-01-01

We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.

Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

International Nuclear Information System (INIS)

Zhou, X.Y.; Li, D.

2000-01-01

This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem

Replica approach to mean-variance portfolio optimization

Science.gov (United States)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

Science.gov (United States)

Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-03-22

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Spot Variance Path Estimation and its Application to High Frequency Jump Testing

NARCIS (Netherlands)

Bos, C.S.; Janus, P.; Koopman, S.J.

2012-01-01

This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to

ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE

OpenAIRE

Abdurakhman, Abdurakhman

2008-01-01

Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

OpenAIRE

Daheng Peng; Fang Zhang

2017-01-01

In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

The asymptotic variance of departures in critically loaded queues

NARCIS (Netherlands)

Al Hanbali, Ahmad; Mandjes, M.R.H.; Nazarathy, Y.; Whitt, W.

2011-01-01

We consider the asymptotic variance of the departure counting process D(t) of the GI/G/1 queue; D(t) denotes the number of departures up to time t. We focus on the case where the system load ϱ equals 1, and prove that the asymptotic variance rate satisfies limt→∞varD(t) / t = λ(1 - 2 / π)(ca2 +

Monte Carlo variance reduction approaches for non-Boltzmann tallies

International Nuclear Information System (INIS)

Booth, T.E.

1992-12-01

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Science.gov (United States)

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Directory of Open Access Journals (Sweden)

Liyun Zhuang

2017-01-01

Full Text Available This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE, which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE. Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance.

Science.gov (United States)

Zhuang, Liyun; Guan, Yepeng

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

Science.gov (United States)

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

An elementary components of variance analysis for multi-center quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1977-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality control (QC) studies. Statistical analysis methods for such studies using an 'analysis of variance with components of variance estimation' are discussed. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Components of variance analysis also provides an intelligent way to combine the results of several QC samples run at different evels, from which we may decide if any component varies systematically with dose level; if not, pooling of estimates becomes possible. We consider several possible relationships of standard deviation to the laboratory mean. Each relationship corresponds to an underlying statistical model, and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine if an appropriate model has been chosen, although the exact functional relationship of standard deviation to lab mean may be difficult to establish. Appropriate graphical display of the data aids in visual understanding of the data. A plot of the ranked standard deviation vs. ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean. (orig.) [de

Explicit formulas for the variance of discounted life-cycle cost

International Nuclear Information System (INIS)

Noortwijk, Jan M. van

2003-01-01

In life-cycle costing analyses, optimal design is usually achieved by minimising the expected value of the discounted costs. As well as the expected value, the corresponding variance may be useful for estimating, for example, the uncertainty bounds of the calculated discounted costs. However, general explicit formulas for calculating the variance of the discounted costs over an unbounded time horizon are not yet available. In this paper, explicit formulas for this variance are presented. They can be easily implemented in software to optimise structural design and maintenance management. The use of the mathematical results is illustrated with some examples

How does variance in fertility change over the demographic transition?

Science.gov (United States)

Hruschka, Daniel J; Burger, Oskar

2016-04-19

Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45-49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. © 2016 The Author(s).

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

Directory of Open Access Journals (Sweden)

Daheng Peng

2017-10-01

Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

Science.gov (United States)

Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

2014-11-01

Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

An elementary components of variance analysis for multi-centre quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1978-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality-control (QC) studies. Simple graphical display of data in the form of histograms is useful but insufficient. The paper discusses statistical analysis methods for such studies using an ''analysis of variance with components of variance estimation''. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Problems with RIA data, e.g. severe non-uniformity of variance and/or departure from a normal distribution violate some of the usual assumptions underlying analysis of variance. In order to correct these problems, it is often necessary to transform the data before analysis by using a logarithmic, square-root, percentile, ranking, RIDIT, ''Studentizing'' or other transformation. Ametric transformations such as ranks or percentiles protect against the undue influence of outlying observations, but discard much intrinsic information. Several possible relationships of standard deviation to the laboratory mean are considered. Each relationship corresponds to an underlying statistical model and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine whether an appropriate model has been chosen, although the exact functional relationship of standard deviation to laboratory mean may be difficult to establish. Appropriate graphical display aids visual understanding of the data. A plot of the ranked standard deviation versus ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean

Using variance structure to quantify responses to perturbation in fish catches

Science.gov (United States)

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

A mean–variance objective for robust production optimization in uncertain geological scenarios

DEFF Research Database (Denmark)

Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

2014-01-01

directly. In the mean–variance bi-criterion objective function risk appears directly, it also considers an ensemble of reservoir models, and has robust optimization as a special extreme case. The mean–variance objective is common for portfolio optimization problems in finance. The Markowitz portfolio...... optimization problem is the original and simplest example of a mean–variance criterion for mitigating risk. Risk is mitigated in oil production by including both the expected NPV (mean of NPV) and the risk (variance of NPV) for the ensemble of possible reservoir models. With the inclusion of the risk...

Asymptotic variance of grey-scale surface area estimators

DEFF Research Database (Denmark)

Svane, Anne Marie

Grey-scale local algorithms have been suggested as a fast way of estimating surface area from grey-scale digital images. Their asymptotic mean has already been described. In this paper, the asymptotic behaviour of the variance is studied in isotropic and sufficiently smooth settings, resulting...... in a general asymptotic bound. For compact convex sets with nowhere vanishing Gaussian curvature, the asymptotics can be described more explicitly. As in the case of volume estimators, the variance is decomposed into a lattice sum and an oscillating term of at most the same magnitude....

Distribution pattern and genetic structure of Aedes zammitii (Diptera: Culicidae) along the Mediterranean and Aegean coasts of Turkey.

Science.gov (United States)

Yavasoglu, Sare Ilknur; Simsek, Fatih Mehmet; Ulger, Celal

2016-06-01

The Mariae species complex, consisting of Aedes mariae, Aedes phoeniciae, and Aedes zammitii, has a limited distribution worldwide. All three species are found in rocky habitats on the coastal areas of Mediterranean countries. Aedes phoeniciae and Ae. zammitii are two members of the Mariae complex that exist in Turkey. The aim of this study was to determine the distribution pattern and genetic structure of Ae. zammitii along the Mediterranean and Aegean regions. For this purpose, larval and adult samples of Ae. zammitii were collected from 19 different rocky habitats along the coastal regions of Antalya, Muğla, Aydın, İzmir, Balıkesir, and Çanakkale provinces. DNA isolation was performed primarily from collected samples, and mitochondrial NADH dehydrogenase 4 (ND4) gene was amplified by polymerase chain reaction. Based on ND4 sequence analyses, 21 haplotypes were detected along the distribution range of the species. Analyses of molecular variance (AMOVA) and spatial analyses of molecular variance (SAMOVA) indicated six groups, and most of the variation was among groups, demonstrating the population structuring at group level. Isolation by distance analyses (IBD) showed a correlation between geographic and genetic distances. © 2016 The Society for Vector Ecology.

Prediction-error variance in Bayesian model updating: a comparative study

Science.gov (United States)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

On the expected value and variance for an estimator of the spatio-temporal product density function

DEFF Research Database (Denmark)

Rodríguez-Corté, Francisco J.; Ghorbani, Mohammad; Mateu, Jorge

Second-order characteristics are used to analyse the spatio-temporal structure of the underlying point process, and thus these methods provide a natural starting point for the analysis of spatio-temporal point process data. We restrict our attention to the spatio-temporal product density function......, and develop a non-parametric edge-corrected kernel estimate of the product density under the second-order intensity-reweighted stationary hypothesis. The expectation and variance of the estimator are obtained, and closed form expressions derived under the Poisson case. A detailed simulation study is presented...... to compare our close expression for the variance with estimated ones for Poisson cases. The simulation experiments show that the theoretical form for the variance gives acceptable values, which can be used in practice. Finally, we apply the resulting estimator to data on the spatio-temporal distribution...

Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

Directory of Open Access Journals (Sweden)

Shanshan Gu

2015-01-01

Full Text Available To solve the problem that dynamic Allan variance (DAVAR with fixed length of window cannot meet the identification accuracy requirement of fiber optic gyro (FOG signal over all time domains, a dynamic Allan variance analysis method with time-variant window length based on fuzzy control is proposed. According to the characteristic of FOG signal, a fuzzy controller with the inputs of the first and second derivatives of FOG signal is designed to estimate the window length of the DAVAR. Then the Allan variances of the signals during the time-variant window are simulated to obtain the DAVAR of the FOG signal to describe the dynamic characteristic of the time-varying FOG signal. Additionally, a performance evaluation index of the algorithm based on radar chart is proposed. Experiment results show that, compared with different fixed window lengths DAVAR methods, the change of FOG signal with time can be identified effectively and the evaluation index of performance can be enhanced by 30% at least by the DAVAR method with time-variant window length based on fuzzy control.

Estimation of noise-free variance to measure heterogeneity.

Directory of Open Access Journals (Sweden)

Tilo Winkler

Full Text Available Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV(2. The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CV(r(2 for comparison with our estimate of noise-free or 'true' heterogeneity (CV(t(2. We found that CV(t(2 was only 5.4% higher than CV(r2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13NN-saline injection. The mean CV(t(2 was 0.10 (range: 0.03-0.30, while the mean CV(2 including noise was 0.24 (range: 0.10-0.59. CV(t(2 was in average 41.5% of the CV(2 measured including noise (range: 17.8-71.2%. The reproducibility of CV(t(2 was evaluated using three repeated PET scans from five subjects. Individual CV(t(2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV(t(2 in PET scans, and may be useful for similar statistical problems in experimental data.

A characterization of optimal portfolios under the tail mean-variance criterion

OpenAIRE

Owadally, I.; Landsman, Z.

2013-01-01

The tail mean–variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean–variance framework. The tail mean–variance criterion...

29 CFR 1926.2 - Variances from safety and health standards.

Science.gov (United States)

2010-07-01

... from safety and health standards. (a) Variances from standards which are, or may be, published in this... 29 Labor 8 2010-07-01 2010-07-01 false Variances from safety and health standards. 1926.2 Section 1926.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...

Allowing variance may enlarge the safe operating space for exploited ecosystems.

Science.gov (United States)

Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

2015-11-17

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

Temperature variance study in Monte-Carlo photon transport theory

International Nuclear Information System (INIS)

Giorla, J.

1985-10-01

We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

Study of the variance of a Monte Carlo calculation. Application to weighting; Etude de la variance d'un calcul de Monte Carlo. Application a la ponderation

Energy Technology Data Exchange (ETDEWEB)

Lanore, Jeanne-Marie [Commissariat a l' Energie Atomique - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Direction des Piles Atomiques, Departement des Etudes de Piles, Service d' Etudes de Protections de Piles (France)

1969-04-15

One of the main difficulties in Monte Carlo computations is the estimation of the results variance. Generally, only an apparent variance can be observed over a few calculations, often very different from the actual variance. By studying a large number of short calculations, the authors have tried to evaluate the real variance, and then to apply the obtained results to the optimization of the computations. The program used is the Poker one-dimensional Monte Carlo program. Calculations are performed in two types of fictitious environments: a body with constant cross section, without absorption, where all shocks are elastic and isotropic; a body with variable cross section (presenting a very pronounced peak and hole), with an anisotropy for high energy elastic shocks, and with the possibility of inelastic shocks (this body presents all the features that can appear in a real case)

The oral microbiome in human immunodeficiency virus (HIV)-positive individuals.

Science.gov (United States)

Kistler, James O; Arirachakaran, Pratanporn; Poovorawan, Yong; Dahlén, Gunnar; Wade, William G

2015-09-01

Human immunodeficiency virus (HIV) infection is associated with a range of oral conditions, and increased numbers of disease-associated microbial species have previously been found in HIV-positive subjects. The aim of this study was to use next-generation sequencing to compare the composition of the oral microbiome in HIV-positive and -negative individuals. Plaque and saliva were collected from 37 HIV-positive individuals and 37 HIV-negative individuals, and their bacterial composition determined by pyrosequencing of partial 16S rRNA genes. A total of 855,222 sequences were analysed. The number of species-level operational taxonomic units (OTUs) detected was significantly lower in the saliva of HIV-positive individuals (mean = 303.3) than in that of HIV-negative individuals (mean = 365.5) (P PCoA) based on community membership (Jaccard index) and structure (Yue and Clayton measure of dissimilarity) showed significant separation of plaque and saliva samples [analysis of molecular variance (AMOVA), P PCoA plots did not show any clear separation based on HIV status. However, AMOVA indicated that there was a significant difference in the community membership of saliva between HIV-positive and -negative groups (P = 0.001). Linear discriminant analysis effect size revealed an OTU identified as Haemophilus parainfluenzae to be significantly associated with HIV-positive individuals, whilst Streptococcus mitis/HOT473 was most significantly associated with HIV-negative individuals. In conclusion, this study has confirmed that the microbial composition of saliva and plaque is different. The oral microbiomes of HIV-positive and -negative individuals were found to be similar overall, although there were minor but significant differences in the composition of the salivary microbiota of the two groups.

Adjustment of heterogenous variances and a calving year effect in ...

African Journals Online (AJOL)

Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models.

Estimating Predictive Variance for Statistical Gas Distribution Modelling

International Nuclear Information System (INIS)

Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

2009-01-01

Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

Estimating integrated variance in the presence of microstructure noise using linear regression

Science.gov (United States)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

Science.gov (United States)

Travers, L M; Simmons, L W; Garcia-Gonzalez, F

2016-05-01

Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

Science.gov (United States)

Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

2009-12-01

Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).

Science.gov (United States)

Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars

2013-10-17

Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro

The derivative based variance sensitivity analysis for the distribution parameters and its computation

International Nuclear Information System (INIS)

Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei

2013-01-01

The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method

A Mean-Variance Criterion for Economic Model Predictive Control of Stochastic Linear Systems

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik

2014-01-01

, the tractability of the resulting optimal control problem is addressed. We use a power management case study to compare different variations of the mean-variance strategy with EMPC based on the certainty equivalence principle. The certainty equivalence strategy is much more computationally efficient than the mean......-variance strategies, but it does not account for the variance of the uncertain parameters. Openloop simulations suggest that a single-stage mean-variance approach yields a significantly lower operating cost than the certainty equivalence strategy. In closed-loop, the single-stage formulation is overly conservative...... be modified to perform almost as well as the two-stage mean-variance formulation. Nevertheless, we argue that the mean-variance approach can be used both as a strategy for evaluating less computational demanding methods such as the certainty equivalence method, and as an individual control strategy when...

Investigating the minimum achievable variance in a Monte Carlo criticality calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros; Eduard Hoogenboom, J. [Delft University of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2008-07-01

The sources of variance in a Monte Carlo criticality calculation are identified and their contributions analyzed. A zero-variance configuration is initially simulated using analytically calculated adjoint functions for biasing. From there, the various sources are analyzed. It is shown that the minimum threshold comes from the fact that the fission source is approximated. In addition, the merits of a simple variance reduction method, such as implicit capture, are shown when compared to an analog simulation. Finally, it is shown that when non-exact adjoint functions are used for biasing, the variance reduction is rather insensitive to the quality of the adjoints, suggesting that the generation of the adjoints should have as low CPU cost as possible, in order to o et the CPU cost in the implementation of the biasing of a simulation. (authors)

Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

Science.gov (United States)

Böing-Messing, Florian; Mulder, Joris

2018-05-03

In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

Analysis of covariance with pre-treatment measurements in randomized trials under the cases that covariances and post-treatment variances differ between groups.

Science.gov (United States)

Funatogawa, Takashi; Funatogawa, Ikuko; Shyr, Yu

2011-05-01

When primary endpoints of randomized trials are continuous variables, the analysis of covariance (ANCOVA) with pre-treatment measurements as a covariate is often used to compare two treatment groups. In the ANCOVA, equal slopes (coefficients of pre-treatment measurements) and equal residual variances are commonly assumed. However, random allocation guarantees only equal variances of pre-treatment measurements. Unequal covariances and variances of post-treatment measurements indicate unequal slopes and, usually, unequal residual variances. For non-normal data with unequal covariances and variances of post-treatment measurements, it is known that the ANCOVA with equal slopes and equal variances using an ordinary least-squares method provides an asymptotically normal estimator for the treatment effect. However, the asymptotic variance of the estimator differs from the variance estimated from a standard formula, and its property is unclear. Furthermore, the asymptotic properties of the ANCOVA with equal slopes and unequal variances using a generalized least-squares method are unclear. In this paper, we consider non-normal data with unequal covariances and variances of post-treatment measurements, and examine the asymptotic properties of the ANCOVA with equal slopes using the variance estimated from a standard formula. Analytically, we show that the actual type I error rate, thus the coverage, of the ANCOVA with equal variances is asymptotically at a nominal level under equal sample sizes. That of the ANCOVA with unequal variances using a generalized least-squares method is asymptotically at a nominal level, even under unequal sample sizes. In conclusion, the ANCOVA with equal slopes can be asymptotically justified under random allocation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Levine's guide to SPSS for analysis of variance

CERN Document Server

Braver, Sanford L; Page, Melanie

2003-01-01

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor desi

An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

Science.gov (United States)

Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

2018-06-01

To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

Mean and variance evolutions of the hot and cold temperatures in Europe

Energy Technology Data Exchange (ETDEWEB)

Parey, Sylvie [EDF/R and D, Chatou Cedex (France); Dacunha-Castelle, D. [Universite Paris 11, Laboratoire de Mathematiques, Orsay (France); Hoang, T.T.H. [Universite Paris 11, Laboratoire de Mathematiques, Orsay (France); EDF/R and D, Chatou Cedex (France)

2010-02-15

In this paper, we examine the trends of temperature series in Europe, for the mean as well as for the variance in hot and cold seasons. To do so, we use as long and homogenous series as possible, provided by the European Climate Assessment and Dataset project for different locations in Europe, as well as the European ENSEMBLES project gridded dataset and the ERA40 reanalysis. We provide a definition of trends that we keep as intrinsic as possible and apply non-parametric statistical methods to analyse them. Obtained results show a clear link between trends in mean and variance of the whole series of hot or cold temperatures: in general, variance increases when the absolute value of temperature increases, i.e. with increasing summer temperature and decreasing winter temperature. This link is reinforced in locations where winter and summer climate has more variability. In very cold or very warm climates, the variability is lower and the link between the trends is weaker. We performed the same analysis on outputs of six climate models proposed by European teams for the 1961-2000 period (1950-2000 for one model), available through the PCMDI portal for the IPCC fourth assessment climate model simulations. The models generally perform poorly and have difficulties in capturing the relation between the two trends, especially in summer. (orig.)

A load factor based mean-variance analysis for fuel diversification

Energy Technology Data Exchange (ETDEWEB)

Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

2009-03-15

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

Origin and consequences of the relationship between protein mean and variance.

Science.gov (United States)

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome.

Analysis of Variance in Statistical Image Processing

Science.gov (United States)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Variance Swap Replication: Discrete or Continuous?

Directory of Open Access Journals (Sweden)

Fabien Le Floc’h

2018-02-01

Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.

Impact of Damping Uncertainty on SEA Model Response Variance

Science.gov (United States)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Male size composition affects male reproductive variance in Atlantic cod Gadus morhua L. spawning aggregations

DEFF Research Database (Denmark)

Bekkevold, Dorte

2006-01-01

Estimates of Atlantic cod Gadus morhua reproductive success, determined using experimental spawning groups and genetic paternity assignment of offspring, showed that within-group variance in male size correlated positively with the degree of male mating skew, predicting a decrease in male reprodu...

Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response

Directory of Open Access Journals (Sweden)

Muqaddas Javed

2014-09-01

Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.

Thermospheric mass density model error variance as a function of time scale

Science.gov (United States)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

International Nuclear Information System (INIS)

Campanelli, Mark; Kacker, Raghu; Kessel, Rüdiger

2013-01-01

A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)

Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

Energy Technology Data Exchange (ETDEWEB)

Shrivastava, Manish [Pacific Northwest National Laboratory, Richland Washington USA; Zhao, Chun [Pacific Northwest National Laboratory, Richland Washington USA; Easter, Richard C. [Pacific Northwest National Laboratory, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Zelenyuk, Alla [Pacific Northwest National Laboratory, Richland Washington USA; Fast, Jerome D. [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Ying [Pacific Northwest National Laboratory, Richland Washington USA; Zhang, Qi [Department of Environmental Toxicology, University of California Davis, California USA; Guenther, Alex [Department of Earth System Science, University of California, Irvine California USA

2016-04-08

We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance

Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes

DEFF Research Database (Denmark)

Højgaard, Bjarne; Vigna, Elena

We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean...... as a mean-variance optimization problem. It is shown that the corresponding mean and variance of the final fund belong to the efficient frontier and also the opposite, that each point on the efficient frontier corresponds to a target-based optimization problem. Furthermore, numerical results indicate...... that the largely adopted lifestyle strategy seems to be very far from being efficient in the mean-variance setting....

ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER

OpenAIRE

SENGUPTA, Jati K.; PARK, Hyung S.

1994-01-01

The hypothesis that the skewness and asymmetry have no significant impact on the mean variance frontier is found to be strongly violated by monthly U.S. data over the period January 1965 through December 1974. This result raises serious doubts whether the common market portifolios such as SP 500, value weighted and equal weighted returns can serve as suitable proxies for meanvariance efficient portfolios in the CAPM framework. A new test for assessing the impact of skewness on the variance fr...

Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

Science.gov (United States)

2008-12-01

slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

1998-01-01

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

The prevalence, prevention and multilevel variance of pressure ulcers in Norwegian hospitals: a cross-sectional study.

Science.gov (United States)

Bredesen, Ida Marie; Bjøro, Karen; Gunningberg, Lena; Hofoss, Dag

2015-01-01

Pressure ulcers are preventable adverse events. Organizational differences may influence the quality of prevention across wards and hospitals. To investigate the prevalence of pressure ulcers, patient-related risk factors, the use of preventive measures and how much of the pressure ulcer variance is at patient, ward and hospital level. A cross-sectional study. Six of the 11 invited hospitals in South-Eastern Norway agreed to participate. Inpatients ≥18 years at 88 somatic hospital wards (N=1209). Patients in paediatric and maternity wards and day surgery patients were excluded. The methodology for pressure ulcer prevalence studies developed by the European Pressure Ulcer Advisory Panel was used, including demographic data, the Braden scale, skin assessment, the location and severity of pressure ulcers and preventive measures. Multilevel analysis was used to investigate variance across hierarchical levels. The prevalence was 18.2% for pressure ulcer category I-IV, 7.2% when category I was excluded. Among patients at risk of pressure ulcers, 44.3% had pressure redistributing support surfaces in bed and only 22.3% received planned repositioning in bed. Multilevel analysis showed that although the dominant part of the variance in the occurrence of pressure ulcers was at patient level there was also a significant amount of variance at ward level. There was, however, no significant variance at hospital level. Pressure ulcer prevalence in this Norwegian sample is similar to comparable European studies. At-risk patients were less likely to receive preventive measures than patients in earlier studies. There was significant variance in the occurrence of pressure ulcers at ward level but not at hospital level, indicating that although interventions for improvement are basically patient related, improvement of procedures and organization at ward level may also be important. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bayesian evaluation of constrained hypotheses on variances of multiple independent groups

NARCIS (Netherlands)

Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.

2017-01-01

Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations

Analysis of conditional genetic effects and variance components in developmental genetics.

Science.gov (United States)

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Development of a treatability variance guidance document for US DOE mixed-waste streams

International Nuclear Information System (INIS)

Scheuer, N.; Spikula, R.; Harms, T.

1990-03-01

In response to the US Department of Energy's (DOE's) anticipated need for variances from the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDRs), a treatability variance guidance document was prepared. The guidance manual is for use by DOE facilities and operations offices. The manual was prepared as a part of an ongoing effort by DOE-EH to provide guidance for the operations offices and facilities to comply with the RCRA (LDRs). A treatability variance is an alternative treatment standard granted by EPA for a restricted waste. Such a variance is not an exemption from the requirements of the LDRs, but rather is an alternative treatment standard that must be met before land disposal. The manual, Guidance For Obtaining Variance From the Treatment Standards of the RCRA Land Disposal Restrictions (1), leads the reader through the process of evaluating whether a variance from the treatment standard is a viable approach and through the data-gathering and data-evaluation processes required to develop a petition requesting a variance. The DOE review and coordination process is also described and model language for use in petitions for DOE radioactive mixed waste (RMW) is provided. The guidance manual focuses on RMW streams, however the manual also is applicable to nonmixed, hazardous waste streams. 4 refs

Individual differences in personality traits reflect structural variance in specific brain regions.

Science.gov (United States)

Gardini, Simona; Cloninger, C Robert; Venneri, Annalena

2009-06-30

Personality dimensions such as novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (PER) are said to be heritable, stable across time and dependent on genetic and neurobiological factors. Recently a better understanding of the relationship between personality traits and brain structures/systems has become possible due to advances in neuroimaging techniques. This Magnetic Resonance Imaging (MRI) study investigated if individual differences in these personality traits reflected structural variance in specific brain regions. A large sample of eighty five young adult participants completed the Three-dimensional Personality Questionnaire (TPQ) and had their brain imaged with MRI. A voxel-based correlation analysis was carried out between individuals' personality trait scores and grey matter volume values extracted from 3D brain scans. NS correlated positively with grey matter volume in frontal and posterior cingulate regions. HA showed a negative correlation with grey matter volume in orbito-frontal, occipital and parietal structures. RD was negatively correlated with grey matter volume in the caudate nucleus and in the rectal frontal gyrus. PER showed a positive correlation with grey matter volume in the precuneus, paracentral lobule and parahippocampal gyrus. These results indicate that individual differences in the main personality dimensions of NS, HA, RD and PER, may reflect structural variance in specific brain areas.

Variance of a product with application to uranium estimation

International Nuclear Information System (INIS)

Lowe, V.W.; Waterman, M.S.

1976-01-01

The U in a container can either be determined directly by NDA or by estimating the weight of material in the container and the concentration of U in this material. It is important to examine the statistical properties of estimating the amount of U by multiplying the estimates of weight and concentration. The variance of the product determines the accuracy of the estimate of the amount of uranium. This paper examines the properties of estimates of the variance of the product of two random variables

Accounting for non-stationary variance in geostatistical mapping of soil properties

NARCIS (Netherlands)

Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.

2018-01-01

Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)

Ulnar variance: its relationship to ulnar foveal morphology and forearm kinematics.

Science.gov (United States)

Kataoka, Toshiyuki; Moritomo, Hisao; Omokawa, Shohei; Iida, Akio; Murase, Tsuyoshi; Sugamoto, Kazuomi

2012-04-01

It is unclear how individual differences in the anatomy of the distal ulna affect kinematics and pathology of the distal radioulnar joint. This study evaluated how ulnar variance relates to ulnar foveal morphology and the pronosupination axis of the forearm. We performed 3-dimensional computed tomography studies in vivo on 28 forearms in maximum supination and pronation to determine the anatomical center of the ulnar distal pole and the forearm pronosupination axis. We calculated the forearm pronosupination axis using a markerless bone registration technique, which determined the pronosupination center as the point where the axis emerges on the distal ulnar surface. We measured the depth of the anatomical center and classified it into 2 types: concave, with a depth of 0.8 mm or more, and flat, with a depth less than 0.8 mm. We examined whether ulnar variance correlated with foveal type and the distance between anatomical and pronosupination centers. A total of 18 cases had a concave-type fovea surrounded by the C-shaped articular facet of the distal pole, and 10 had a flat-type fovea with a flat surface without evident central depression. Ulnar variance of the flat type was 3.5 ± 1.2 mm, which was significantly greater than the 1.2 ± 1.1 mm of the concave type. Ulnar variance positively correlated with distance between the anatomical and pronosupination centers. Flat-type ulnar heads have a significantly greater ulnar variance than concave types. The pronosupination axis passes through the ulnar head more medially and farther from the anatomical center with increasing ulnar variance. This study suggests that ulnar variance is related in part to foveal morphology and pronosupination axis. This information provides a starting point for future studies investigating how foveal morphology relates to distal ulnar problems. Copyright © 2012 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

A Surface-Layer Study of the Transport and Dissipation of Turbulent Kinetic Energy and the Variances of Temperature, Humidity and CO_2

Science.gov (United States)

Hackerott, João A.; Bakhoday Paskyabi, Mostafa; Reuder, Joachim; de Oliveira, Amauri P.; Kral, Stephan T.; Marques Filho, Edson P.; Mesquita, Michel dos Santos; de Camargo, Ricardo

2017-11-01

We discuss scalar similarities and dissimilarities based on analysis of the dissipation terms in the variance budget equations, considering the turbulent kinetic energy and the variances of temperature, specific humidity and specific CO_2 content. For this purpose, 124 high-frequency sampled segments are selected from the Boundary Layer Late Afternoon and Sunset Turbulence experiment. The consequences of dissipation similarity in the variance transport are also discussed and quantified. The results show that, for the convective atmospheric surface layer, the non-dimensional dissipation terms can be expressed in the framework of Monin-Obukhov similarity theory and are independent of whether the variable is temperature or moisture. The scalar similarity in the dissipation term implies that the characteristic scales of the atmospheric surface layer can be estimated from the respective rate of variance dissipation, the characteristic scale of temperature, and the dissipation rate of temperature variance.

The efficiency of the crude oil markets: Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie, E-mail: acharles@audencia.co [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier, E-mail: olivier.darne@univ-nantes.f [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable.

The efficiency of the crude oil markets. Evidence from variance ratio tests

International Nuclear Information System (INIS)

Charles, Amelie; Darne, Olivier

2009-01-01

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

The efficiency of the crude oil markets. Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

Variance reduction methods applied to deep-penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.

1984-01-01

All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course

Cumulative prospect theory and mean variance analysis. A rigorous comparison

OpenAIRE

Hens, Thorsten; Mayer, Janos

2012-01-01

We compare asset allocations derived for cumulative prospect theory(CPT) based on two different methods: Maximizing CPT along the mean–variance efficient frontier and maximizing it without that restriction. We find that with normally distributed returns the difference is negligible. However, using standard asset allocation data of pension funds the difference is considerable. Moreover, with derivatives like call options the restriction to the mean-variance efficient frontier results in a siza...

Variance in exposed perturbations impairs retention of visuomotor adaptation.

Science.gov (United States)

Canaveral, Cesar Augusto; Danion, Frédéric; Berrigan, Félix; Bernier, Pierre-Michel

2017-11-01

Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay. NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

2010-01-01

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-01-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

On the mean and variance of the writhe of random polygons

International Nuclear Information System (INIS)

Portillo, J; Scharein, R; Arsuaga, J; Vazquez, M; Diao, Y

2011-01-01

We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an 'ideal' conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n) behaves as a linear function of the length of the equilateral random polygon.

On the mean and variance of the writhe of random polygons.

Science.gov (United States)

Portillo, J; Diao, Y; Scharein, R; Arsuaga, J; Vazquez, M

We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an "ideal" conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n ) behaves as a linear function of the length of the equilateral random polygon.

Variance in population firing rate as a measure of slow time-scale correlation

Directory of Open Access Journals (Sweden)

Adam C. Snyder

2013-12-01

Full Text Available Correlated variability in the spiking responses of pairs of neurons, also known as spike count correlation, is a key indicator of functional connectivity and a critical factor in population coding. Underscoring the importance of correlation as a measure for cognitive neuroscience research is the observation that spike count correlations are not fixed, but are rather modulated by perceptual and cognitive context. Yet while this context fluctuates from moment to moment, correlation must be calculated over multiple trials. This property undermines its utility as a dependent measure for investigations of cognitive processes which fluctuate on a trial-to-trial basis, such as selective attention. A measure of functional connectivity that can be assayed on a moment-to-moment basis is needed to investigate the single-trial dynamics of populations of spiking neurons. Here, we introduce the measure of population variance in normalized firing rate for this goal. We show using mathematical analysis, computer simulations and in vivo data how population variance in normalized firing rate is inversely related to the latent correlation in the population, and how this measure can be used to reliably classify trials from different typical correlation conditions, even when firing rate is held constant. We discuss the potential advantages for using population variance in normalized firing rate as a dependent measure for both basic and applied neuroscience research.

Genetic diversity of Mycosphaerella fijiensis in Brazil analyzed using an ERIC-PCR marker.

Science.gov (United States)

Silva, G F; Paixão, R D V; Queiroz, C B; Santana, M F; Souza, A; Sousa, N R; Hanada, R E; Gasparotto, L

2014-09-26

The Enterobacterial repetitive intergenic consensus (ERIC) marker was used to analyze the genetic variability of Mycosphaerella fijiensis, the causative agent of Black Sigatoka disease in banana plants. A total of 123 isolates were used, which were divided into populations based on their original hosts and collection sites in Brazil. A total of 9 loci were amplified, 77.8% of which were found to be polymorphic. The genetic diversity found in the population was 0.20. Analysis of molecular variance (AMOVA) demonstrated that the highest level of genetic variation is within populations. Cluster analysis revealed three main groups in Brazil, with no correlation between geographic and genetic distance.

Gravity interpretation of dipping faults using the variance analysis method

International Nuclear Information System (INIS)

Essa, Khalid S

2013-01-01

A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)

Perspective projection for variance pose face recognition from camera calibration

Science.gov (United States)

Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

2016-04-01

Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

Variance-to-mean method generalized by linear difference filter technique

International Nuclear Information System (INIS)

Hashimoto, Kengo; Ohsaki, Hiroshi; Horiguchi, Tetsuo; Yamane, Yoshihiro; Shiroya, Seiji

1998-01-01

The conventional variance-to-mean method (Feynman-α method) seriously suffers the divergency of the variance under such a transient condition as a reactor power drift. Strictly speaking, then, the use of the Feynman-α is restricted to a steady state. To apply the method to more practical uses, it is desirable to overcome this kind of difficulty. For this purpose, we propose an usage of higher-order difference filter technique to reduce the effect of the reactor power drift, and derive several new formulae taking account of the filtering. The capability of the formulae proposed was demonstrated through experiments in the Kyoto University Critical Assembly. The experimental results indicate that the divergency of the variance can be effectively suppressed by the filtering technique, and that the higher-order filter becomes necessary with increasing variation rate in power

The impact of grid and spectral nudging on the variance of the near-surface wind speed

DEFF Research Database (Denmark)

Vincent, Claire Louise; Hahmann, Andrea N.

2015-01-01

Grid and spectral nudging are effective ways of preventing drift from large scale weather patterns in regional climate models. However, the effect of nudging on the wind-speed variance is unclear. In this study, the impact of grid and spectral nudging on near-surface and upper boundary layer wind...... nudging at and above 1150 m above ground level (AGL). Nested 5 km simulations are not nudged directly, but inherit boundary conditions from the 15 km experiments. Spatial and temporal spectra show that grid nudging causes smoothing of the wind in the 15 km domain at all wavenumbers, both at 1150 m AGL...... and near the surface where nudging is not applied directly, while spectral nudging mainly affects longer wavenumbers. Maps of mesoscale variance show spatial smoothing for both grid and spectral nudging, although the effect is less pronounced for spectral nudging. On the inner, 5 km domain, an indirect...

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

Science.gov (United States)

Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

2016-01-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

Multi-Period Mean-Variance Portfolio Selection with Uncertain Time Horizon When Returns Are Serially Correlated

Directory of Open Access Journals (Sweden)

Ling Zhang

2012-01-01

Full Text Available We study a multi-period mean-variance portfolio selection problem with an uncertain time horizon and serial correlations. Firstly, we embed the nonseparable multi-period optimization problem into a separable quadratic optimization problem with uncertain exit time by employing the embedding technique of Li and Ng (2000. Then we convert the later into an optimization problem with deterministic exit time. Finally, using the dynamic programming approach, we explicitly derive the optimal strategy and the efficient frontier for the dynamic mean-variance optimization problem. A numerical example with AR(1 return process is also presented, which shows that both the uncertainty of exit time and the serial correlations of returns have significant impacts on the optimal strategy and the efficient frontier.

Risk implications of renewable support instruments: Comparative analysis of feed-in tariffs and premiums using a mean–variance approach

International Nuclear Information System (INIS)

Kitzing, Lena

2014-01-01

Different support instruments for renewable energy expose investors differently to market risks. This has implications on the attractiveness of investment. We use mean–variance portfolio analysis to identify the risk implications of two support instruments: feed-in tariffs and feed-in premiums. Using cash flow analysis, Monte Carlo simulations and mean–variance analysis, we quantify risk-return relationships for an exemplary offshore wind park in a simplified setting. We show that feed-in tariffs systematically require lower direct support levels than feed-in premiums while providing the same attractiveness for investment, because they expose investors to less market risk. These risk implications should be considered when designing policy schemes. - Highlights: • Mean–variance portfolio approach to analyse risk implications of policy instruments. • We show that feed-in tariffs require lower support levels than feed-in premiums. • This systematic effect stems from the lower exposure of investors to market risk. • We created a stochastic model for an exemplary offshore wind park in West Denmark. • We quantify risk-return, Sharpe Ratios and differences in required support levels

Biological Variance in Agricultural Products. Theoretical Considerations

NARCIS (Netherlands)

Tijskens, L.M.M.; Konopacki, P.

2003-01-01

The food that we eat is uniform neither in shape or appearance nor in internal composition or content. Since technology became increasingly important, the presence of biological variance in our food became more and more of a nuisance. Techniques and procedures (statistical, technical) were

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

The pricing of long and short run variance and correlation risk in stock returns

NARCIS (Netherlands)

Cosemans, M.

2011-01-01

This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Science.gov (United States)

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

Application of a CADIS-like variance reduction technique to electron transport

International Nuclear Information System (INIS)

Dionne, B.; Haghighat, A.

2004-01-01

This paper studies the use of approximate deterministic importance functions to calculate the lower-weight bounds of the MCNP5 weight-window variance reduction technique when applied to electron transport simulations. This approach follows the CADIS (Consistent Adjoint Driven Importance Sampling) methodology developed for neutral particles shielding calculations. The importance functions are calculated using the one-dimensional CEPXS/ONELD code package. Considering a simple 1-D problem, this paper shows that our methodology can produce speedups up to ∼82 using an approximate electron importance function distributions computed in ∼8 seconds. (author)

Studying Variance in the Galactic Ultra-compact Binary Population

Science.gov (United States)

Larson, Shane; Breivik, Katelyn

2017-01-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

Variance estimates for transport in stochastic media by means of the master equation

International Nuclear Information System (INIS)

Pautz, S. D.; Franke, B. C.; Prinja, A. K.

2013-01-01

The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

Forecasting the variance and return of Mexican financial series with symmetric GARCH models

Directory of Open Access Journals (Sweden)

Fátima Irina VILLALBA PADILLA

2013-03-01

Full Text Available The present research shows the application of the generalized autoregresive conditional heteroskedasticity models (GARCH in order to forecast the variance and return of the IPC, the EMBI, the weighted-average government funding rate, the fix exchange rate and the Mexican oil reference, as important tools for investment decisions. Forecasts in-sample and out-of-sample are performed. The covered period involves from 2005 to 2011.

Variance of discharge estimates sampled using acoustic Doppler current profilers from moving boats

Science.gov (United States)

Garcia, Carlos M.; Tarrab, Leticia; Oberg, Kevin; Szupiany, Ricardo; Cantero, Mariano I.

2012-01-01

This paper presents a model for quantifying the random errors (i.e., variance) of acoustic Doppler current profiler (ADCP) discharge measurements from moving boats for different sampling times. The model focuses on the random processes in the sampled flow field and has been developed using statistical methods currently available for uncertainty analysis of velocity time series. Analysis of field data collected using ADCP from moving boats from three natural rivers of varying sizes and flow conditions shows that, even though the estimate of the integral time scale of the actual turbulent flow field is larger than the sampling interval, the integral time scale of the sampled flow field is on the order of the sampling interval. Thus, an equation for computing the variance error in discharge measurements associated with different sampling times, assuming uncorrelated flow fields is appropriate. The approach is used to help define optimal sampling strategies by choosing the exposure time required for ADCPs to accurately measure flow discharge.

Population genetic dynamics of three-spined sticklebacks (Gasterosteus aculeatus) in anthropogenic altered habitats.

Science.gov (United States)

Scharsack, Joern P; Schweyen, Hannah; Schmidt, Alexander M; Dittmar, Janine; Reusch, Thorsten Bh; Kurtz, Joachim

2012-06-01

In industrialized and/or agriculturally used landscapes, inhabiting species are exposed to a variety of anthropogenic changes in their environments. Genetic diversity may be reduced if populations encounter founder events, bottlenecks, or isolation. Conversely, genetic diversity may increase if populations adapt to changes in selective regimes in newly created habitats. With the present study, genetic variability of 918 sticklebacks from 43 samplings (21.3 ± 3.8 per sample) at 36 locations from cultivated landscapes in Northwest Germany was analyzed at nine neutral microsatellite loci. To test if differentiation is influenced by habitat alterations, sticklebacks were collected from ancient running waters and adjacent artificial stagnant waters, from brooks with salt water inflow of anthropogenic and natural origin and adjacent freshwater sites. Overall population structure was dominated by isolation by distance (IBD), which was significant across all populations, and analysis of molecular variance (AMOVA) revealed that 10.6% of the variation was explained by river catchment area. Populations in anthropogenic modified habitats deviated from the general IBD structure and in the AMOVA, grouping by habitat type running/stagnant water explained 4.9% of variation and 1.4% of the variation was explained by salt-/freshwater habitat. Sticklebacks in salt-polluted water systems seem to exhibit elevated migratory activity between fresh- and saltwater habitats, reducing IBD. In other situations, populations showed distinct signs of genetic isolation, which in some locations was attributed to mechanical migration barriers, but in others to potential anthropogenic induced bottleneck or founder effects. The present study shows that anthropogenic habitat alterations may have diverse effects on the population genetic structure of inhabiting species. Depending on the type of habitat change, increased genetic differentiation, diversification, or isolation are possible consequences.

Visual SLAM Using Variance Grid Maps

Science.gov (United States)

Howard, Andrew B.; Marks, Tim K.

2011-01-01

An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

Temporal variance reverses the impact of high mean intensity of stress in climate change experiments.

Science.gov (United States)

Benedetti-Cecchi, Lisandro; Bertocci, Iacopo; Vaselli, Stefano; Maggi, Elena

2006-10-01

Extreme climate events produce simultaneous changes to the mean and to the variance of climatic variables over ecological time scales. While several studies have investigated how ecological systems respond to changes in mean values of climate variables, the combined effects of mean and variance are poorly understood. We examined the response of low-shore assemblages of algae and invertebrates of rocky seashores in the northwest Mediterranean to factorial manipulations of mean intensity and temporal variance of aerial exposure, a type of disturbance whose intensity and temporal patterning of occurrence are predicted to change with changing climate conditions. Effects of variance were often in the opposite direction of those elicited by changes in the mean. Increasing aerial exposure at regular intervals had negative effects both on diversity of assemblages and on percent cover of filamentous and coarsely branched algae, but greater temporal variance drastically reduced these effects. The opposite was observed for the abundance of barnacles and encrusting coralline algae, where high temporal variance of aerial exposure either reversed a positive effect of mean intensity (barnacles) or caused a negative effect that did not occur under low temporal variance (encrusting algae). These results provide the first experimental evidence that changes in mean intensity and temporal variance of climatic variables affect natural assemblages of species interactively, suggesting that high temporal variance may mitigate the ecological impacts of ongoing and predicted climate changes.

Genetic and environmental variance in content dimensions of the MMPI.

Science.gov (United States)

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

Science.gov (United States)

Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

2015-10-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

Heritability, variance components and genetic advance of some ...

African Journals Online (AJOL)

Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.

Modality-Driven Classification and Visualization of Ensemble Variance

Energy Technology Data Exchange (ETDEWEB)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

2016-10-01

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

Variance Risk Premia on Stocks and Bonds

DEFF Research Database (Denmark)

Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea

Investors in fixed income markets are willing to pay a very large premium to be hedged against shocks in expected volatility and the size of this premium can be studied through variance swaps. Using thirty years of option and high-frequency data, we document the following novel stylized facts...

Spatially tuned normalization explains attention modulation variance within neurons.

Science.gov (United States)

Ni, Amy M; Maunsell, John H R

2017-09-01

Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism. NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical

Feasibility of speckle variance OCT for imaging cutaneous microvasculature regeneration during healing of wounds in diabetic mice

Science.gov (United States)

Sharma, P.; Kumawat, J.; Kumar, S.; Sahu, K.; Verma, Y.; Gupta, P. K.; Rao, K. D.

2018-02-01

We report on a study to assess the feasibility of a swept source-based speckle variance optical coherence tomography setup for monitoring cutaneous microvasculature. Punch wounds created in the ear pinnae of diabetic mice were monitored at different times post wounding to assess the structural and vascular changes. It was observed that the epithelium thickness increases post wounding and continues to be thick even after healing. Also, the wound size assessed by vascular images is larger than the physical wound size. The results show that the developed speckle variance optical coherence tomography system can be used to monitor vascular regeneration during wound healing in diabetic mice.

On Mean-Variance Hedging of Bond Options with Stochastic Risk Premium Factor

NARCIS (Netherlands)

Aihara, ShinIchi; Bagchi, Arunabha; Kumar, Suresh K.

2014-01-01

We consider the mean-variance hedging problem for pricing bond options using the yield curve as the observation. The model considered contains infinite-dimensional noise sources with the stochastically- varying risk premium. Hence our model is incomplete. We consider mean-variance hedging under the

Problems of variance reduction in the simulation of random variables

International Nuclear Information System (INIS)

Lessi, O.

1987-01-01

The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced

Mean-variance portfolio allocation with a value at risk constraint

OpenAIRE

Enrique Sentana

2001-01-01

In this Paper, I first provide a simple unifying approach to static Mean-Variance analysis and Value at Risk, which highlights their similarities and differences. Then I use it to explain how fund managers can take investment decisions that satisfy the VaR restrictions imposed on them by regulators, within the well-known Mean-Variance allocation framework. I do so by introducing a new type of line to the usual mean-standard deviation diagram, called IsoVaR,which represents all the portfolios ...

Variance-based sensitivity analysis for wastewater treatment plant modelling.

Science.gov (United States)

Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

2014-02-01

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

Fundamentals of exploratory analysis of variance

CERN Document Server

Hoaglin, David C; Tukey, John W

2009-01-01

The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

Science.gov (United States)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

Pricing perpetual American options under multiscale stochastic elasticity of variance

International Nuclear Information System (INIS)

Yoon, Ji-Hun

2015-01-01

Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk

Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

Science.gov (United States)

Baek, Eun Kyeng; Ferron, John M

2013-03-01

Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

Directory of Open Access Journals (Sweden)

Neslihan Fidan Keçeci

2016-10-01

Full Text Available The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

Science.gov (United States)

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

Science.gov (United States)

Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

2015-01-01

Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

Population structure and genetic diversity of Indian Major Carp, Labeo rohita (Hamilton, 1822) from three phylo-geographically isolated riverine ecosystems of India as revealed by mtDNA cytochrome b region sequences.

Science.gov (United States)

Behera, Bijay Kumar; Baisvar, Vishwamitra Singh; Kunal, Swaraj Priyaranjan; Meena, Dharmendra Kumar; Panda, Debarata; Pakrashi, Sudip; Paria, Prasenjit; Das, Pronob; Bhakta, Dibakar; Debnath, Dipesh; Roy, Suvra; Suresh, V R; Jena, J K

2018-03-01

The population structure and genetic diversity of Rohu (Labeo rohita Hamilton, 1822) was studied by analysis of the partial sequences of mitochondrial DNA cytochrome b region. We examined 133 samples collected from six locations in three geographically isolated rivers of India. Analysis of 11 haplotypes showed low haplotype diversity (0.00150), nucleotide diversity (π) (0.02884) and low heterogeneity value (0.00374). Analysis of molecular variance (AMOVA) revealed the genetic diversity of L. rohita within population is very high than between the populations. The Fst scores (-0.07479 to 0.07022) were the indication of low genetic structure of L. rohita populations of three rivers of India. Conspicuously, Farakka-Bharuch population pair Fst score of 0.0000, although the sampling sites are from different rivers. The phylogenetic reconstruction of unique haplotypes revealed sharing of a single central haplotype (Hap_1) by all the six populations with a point mutations ranging from 1-25 nucleotides.

Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

Science.gov (United States)

Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

2013-09-01

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also

Use of EST-SSR Markers for Evaluating Genetic Diversity and Fingerprinting Celery (Apium graveolens L. Cultivars

Directory of Open Access Journals (Sweden)

Nan Fu

2014-02-01

Full Text Available Celery (Apium graveolens L. is one of the most economically important vegetables worldwide, but genetic and genomic resources supporting celery molecular breeding are quite limited, thus few studies on celery have been conducted so far. In this study we made use of simple sequence repeat (SSR markers generated from previous celery transcriptome sequencing and attempted to detect the genetic diversity and relationships of commonly used celery accessions and explore the efficiency of the primers used for cultivars identification. Analysis of molecular variance (AMOVA of Apium graveolens L. var. dulce showed that approximately 43% of genetic diversity was within accessions, 45% among accessions, and 22% among horticultural types. The neighbor-joining tree generated by unweighted pair group method with arithmetic mean (UPGMA, and population structure analysis, as well as principal components analysis (PCA, separated the cultivars into clusters corresponding to the geographical areas where they originated. Genetic distance analysis suggested that genetic variation within Apium graveolens was quite limited. Genotypic diversity showed any combinations of 55 genic SSRs were able to distinguish the genotypes of all 30 accessions.

Variance estimation for complex indicators of poverty and inequality using linearization techniques

Directory of Open Access Journals (Sweden)

Guillaume Osier

2009-12-01

Full Text Available The paper presents the Eurostat experience in calculating measures of precision, including standard errors, confidence intervals and design effect coefficients - the ratio of the variance of a statistic with the actual sample design to the variance of that statistic with a simple random sample of same size - for the "Laeken" indicators, that is, a set of complex indicators of poverty and inequality which had been set out in the framework of the EU-SILC project (European Statistics on Income and Living Conditions. The Taylor linearization method (Tepping, 1968; Woodruff, 1971; Wolter, 1985; Tille, 2000 is actually a well-established method to obtain variance estimators for nonlinear statistics such as ratios, correlation or regression coefficients. It consists of approximating a nonlinear statistic with a linear function of the observations by using first-order Taylor Series expansions. Then, an easily found variance estimator of the linear approximation is used as an estimator of the variance of the nonlinear statistic. Although the Taylor linearization method handles all the nonlinear statistics which can be expressed as a smooth function of estimated totals, the approach fails to encompass the "Laeken" indicators since the latter are having more complex mathematical expressions. Consequently, a generalized linearization method (Deville, 1999, which relies on the concept of influence function (Hampel, Ronchetti, Rousseeuw and Stahel, 1986, has been implemented. After presenting the EU-SILC instrument and the main target indicators for which variance estimates are needed, the paper elaborates on the main features of the linearization approach based on influence functions. Ultimately, estimated standard errors, confidence intervals and design effect coefficients obtained from this approach are presented and discussed.

The role of respondents’ comfort for variance in stated choice surveys

DEFF Research Database (Denmark)

Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

2017-01-01

they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

International Nuclear Information System (INIS)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

Energy Technology Data Exchange (ETDEWEB)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs.

On discrete stochastic processes with long-lasting time dependence in the variance

Science.gov (United States)

Queirós, S. M. D.

2008-11-01

In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

Determinations of dose mean of specific energy for conventional x-rays by variance-measurements

International Nuclear Information System (INIS)

Forsberg, B.; Jensen, M.; Lindborg, L.; Samuelson, G.

1978-05-01

The dose mean value (zeta) of specific energy of a single event distribution is related to the variance of a multiple event distribution in a simple way. It is thus possible to determine zeta from measurements in high dose rates through observations of the variations in the ionization current from for instance an ionization chamber, if other parameters contribute negligibly to the total variance. With this method is has earlier been possible to obtain results down to about 10 nm in a beam of Co60-γ rays, which is one order of magnitude smaller than the sizes obtainable with the traditional technique. This advantage together with the suggestion that zeta could be an important parameter in radiobiology make further studies of the applications of the technique motivated. So far only data from measurements in beams of a radioactive nuclide has been reported. This paper contains results from measurements in a highly stabilized X-ray beam. The preliminary analysis shows that the variance technique has given reasonable results for object sizes in the region of 0.08 μm to 20 μm (100 kV, 1.6 Al, HVL 0.14 mm Cu). The results were obtained with a proportional counter except for the larger object sizes, where an ionization chamber was used. The measurements were performed at dose rates between 1 Gy/h and 40 Gy/h. (author)

Heteroscedastic Tests Statistics for One-Way Analysis of Variance: The Trimmed Means and Hall's Transformation Conjunction

Science.gov (United States)

Luh, Wei-Ming; Guo, Jiin-Huarng

2005-01-01

To deal with nonnormal and heterogeneous data for the one-way fixed effect analysis of variance model, the authors adopted a trimmed means method in conjunction with Hall's invertible transformation into a heteroscedastic test statistic (Alexander-Govern test or Welch test). The results of simulation experiments showed that the proposed technique…

78 FR 14122 - Revocation of Permanent Variances

Science.gov (United States)

2013-03-04

... Douglas Fir planking had to have at least a 1,900 fiber stress and 1,900,000 modulus of elasticity, while the Yellow Pine planking had to have at least 2,500 fiber stress and 2,000,000 modulus of elasticity... the permanent variances, and affected employees, to submit written data, views, and arguments...

Optimal control of LQG problem with an explicit trade-off between mean and variance

Science.gov (United States)

Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

2011-12-01

For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

Theoretical and practical study of the variance and efficiency of a Monte Carlo calculation due to Russian roulette

International Nuclear Information System (INIS)

Hoogenboom, J. E.

2004-01-01

Although Russian roulette is applied very often in Monte Carlo calculations, not much literature exists on its quantitative influence on the variance and efficiency of a Monte Carlo calculation. Elaborating on the work of Lux and Koblinger using moment equations, new relevant equations are derived to calculate the variance of a Monte Carlo simulation using Russian roulette. To demonstrate its practical application the theory is applied to a simplified transport model resulting in explicit analytical expressions for the variance of a Monte Carlo calculation and for the expected number of collisions per history. From these expressions numerical results are shown and compared with actual Monte Carlo calculations, showing an excellent agreement. By considering the number of collisions in a Monte Carlo calculation as a measure of the CPU time, also the efficiency of the Russian roulette can be studied. It opens the way for further investigations, including optimization of Russian roulette parameters. (authors)

ACCOUNTING FOR COSMIC VARIANCE IN STUDIES OF GRAVITATIONALLY LENSED HIGH-REDSHIFT GALAXIES IN THE HUBBLE FRONTIER FIELD CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Robertson, Brant E.; Stark, Dan P. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Ellis, Richard S. [Department of Astronomy, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States); Dunlop, James S.; McLure, Ross J.; McLeod, Derek, E-mail: brant@email.arizona.edu [Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ (United Kingdom)

2014-12-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ∼35% at redshift z ∼ 7 to ≳ 65% at z ∼ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program.

ACCOUNTING FOR COSMIC VARIANCE IN STUDIES OF GRAVITATIONALLY LENSED HIGH-REDSHIFT GALAXIES IN THE HUBBLE FRONTIER FIELD CLUSTERS

International Nuclear Information System (INIS)

Robertson, Brant E.; Stark, Dan P.; Ellis, Richard S.; Dunlop, James S.; McLure, Ross J.; McLeod, Derek

2014-01-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ∼35% at redshift z ∼ 7 to ≳ 65% at z ∼ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program

Accounting for Cosmic Variance in Studies of Gravitationally Lensed High-redshift Galaxies in the Hubble Frontier Field Clusters

Science.gov (United States)

Robertson, Brant E.; Ellis, Richard S.; Dunlop, James S.; McLure, Ross J.; Stark, Dan P.; McLeod, Derek

2014-12-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ~35% at redshift z ~ 7 to >~ 65% at z ~ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program.

Deterministic mean-variance-optimal consumption and investment

DEFF Research Database (Denmark)

Christiansen, Marcus; Steffensen, Mogens

2013-01-01

In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...

Estimates for Genetic Variance Components in Reciprocal Recurrent Selection in Populations Derived from Maize Single-Cross Hybrids

Directory of Open Access Journals (Sweden)

Matheus Costa dos Reis

2014-01-01

Full Text Available This study was carried out to obtain the estimates of genetic variance and covariance components related to intra- and interpopulation in the original populations (C0 and in the third cycle (C3 of reciprocal recurrent selection (RRS which allows breeders to define the best breeding strategy. For that purpose, the half-sib progenies of intrapopulation (P11 and P22 and interpopulation (P12 and P21 from populations 1 and 2 derived from single-cross hybrids in the 0 and 3 cycles of the reciprocal recurrent selection program were used. The intra- and interpopulation progenies were evaluated in a 10×10 triple lattice design in two separate locations. The data for unhusked ear weight (ear weight without husk and plant height were collected. All genetic variance and covariance components were estimated from the expected mean squares. The breakdown of additive variance into intrapopulation and interpopulation additive deviations (στ2 and the covariance between these and their intrapopulation additive effects (CovAτ found predominance of the dominance effect for unhusked ear weight. Plant height for these components shows that the intrapopulation additive effect explains most of the variation. Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs.

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

2009-01-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

AN ADAPTIVE OPTIMAL KALMAN FILTER FOR STOCHASTIC VIBRATION CONTROL SYSTEM WITH UNKNOWN NOISE VARIANCES

Institute of Scientific and Technical Information of China (English)

Li Shu; Zhuo Jiashou; Ren Qingwen

2000-01-01

In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.

Some asymptotic theory for variance function smoothing | Kibua ...

African Journals Online (AJOL)

Simple selection of the smoothing parameter is suggested. Both homoscedastic and heteroscedastic regression models are considered. Keywords: Asymptotic, Smoothing, Kernel, Bandwidth, Bias, Variance, Mean squared error, Homoscedastic, Heteroscedastic. > East African Journal of Statistics Vol. 1 (1) 2005: pp. 9-22 ...

Properties of realized variance under alternative sampling schemes

NARCIS (Netherlands)

Oomen, R.C.A.

2006-01-01

This paper investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise. Different from the existing literature, the analysis relies on a pure jump process for high frequency security prices and explicitly distinguishes among alternative

Intragenomic sequence variation at the ITS1 - ITS2 region and at the 18S and 28S nuclear ribosomal DNA genes of the New Zealand mud snail, Potamopyrgus antipodarum (Hydrobiidae: mollusca)

Science.gov (United States)

Hoy, Marshal S.; Rodriguez, Rusty J.

2013-01-01

Molecular genetic analysis was conducted on two populations of the invasive non-native New Zealand mud snail (Potamopyrgus antipodarum), one from a freshwater ecosystem in Devil's Lake (Oregon, USA) and the other from an ecosystem of higher salinity in the Columbia River estuary (Hammond Harbor, Oregon, USA). To elucidate potential genetic differences between the two populations, three segments of nuclear ribosomal DNA (rDNA), the ITS1-ITS2 regions and the 18S and 28S rDNA genes were cloned and sequenced. Variant sequences within each individual were found in all three rDNA segments. Folding models were utilized for secondary structure analysis and results indicated that there were many sequences which contained structure-altering polymorphisms, which suggests they could be nonfunctional pseudogenes. In addition, analysis of molecular variance (AMOVA) was used for hierarchical analysis of genetic variance to estimate variation within and among populations and within individuals. AMOVA revealed significant variation in the ITS region between the populations and among clones within individuals, while in the 5.8S rDNA significant variation was revealed among individuals within the two populations. High levels of intragenomic variation were found in the ITS regions, which are known to be highly variable in many organisms. More interestingly, intragenomic variation was also found in the 18S and 28S rDNA, which has rarely been observed in animals and is so far unreported in Mollusca. We postulate that in these P. antipodarum populations the effects of concerted evolution are diminished due to the fact that not all of the rDNA genes in their polyploid genome should be essential for sustaining cellular function. This could lead to a lessening of selection pressures, allowing mutations to accumulate in some copies, changing them into variant sequences.                   

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

Right on Target, or Is it? The Role of Distributional Shape in Variance Targeting

Directory of Open Access Journals (Sweden)

Stanislav Anatolyev

2015-08-01

Full Text Available Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML estimation with variance targeting, which reduces the degree of parameterization and facilitates estimation. We compare the two approaches and investigate, via simulations, how non-normality features of the return distribution affect the quality of estimation of the volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions are more precisely estimated when no variance targeting is employed. Bias properties are exacerbated for a heavier-tailed distribution of standardized returns, while the distributional asymmetry has little or moderate impact, these phenomena tending to be more pronounced under variance targeting. Some effects further intensify if one uses ML based on a leptokurtic distribution in place of normal QML. The sample size has also a more favorable effect on estimation precision when no variance targeting is used. Thus, if computational costs are not prohibitive, variance targeting should probably be avoided.

Variance analysis refines overhead cost control.

Science.gov (United States)

Cooper, J C; Suver, J D

1992-02-01

Many healthcare organizations may not fully realize the benefits of standard cost accounting techniques because they fail to routinely report volume variances in their internal reports. If overhead allocation is routinely reported on internal reports, managers can determine whether billing remains current or lost charges occur. Healthcare organizations' use of standard costing techniques can lead to more realistic performance measurements and information system improvements that alert management to losses from unrecovered overhead in time for corrective action.

Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function

OpenAIRE

Kerstens, Kristiaan; Mounier, Amine; Van de Woestyne, Ignace

2008-01-01

The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio fro...

Improved estimation of the variance in Monte Carlo criticality calculations

International Nuclear Information System (INIS)

Hoogenboom, J. Eduard

2008-01-01

Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k eff results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k eff will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k eff are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)

Improved estimation of the variance in Monte Carlo criticality calculations

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)

2008-07-01

Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k{sub eff} results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k{sub eff} will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k{sub eff} are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

Becker, T.L.; Larsen, E.W.

2011-01-01

This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

Science.gov (United States)

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

2014-01-01

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...

An entropy approach to size and variance heterogeneity

NARCIS (Netherlands)

Balasubramanyan, L.; Stefanou, S.E.; Stokes, J.R.

2012-01-01

In this paper, we investigate the effect of bank size differences on cost efficiency heterogeneity using a heteroskedastic stochastic frontier model. This model is implemented by using an information theoretic maximum entropy approach. We explicitly model both bank size and variance heterogeneity

Understanding the Degrees of Freedom of Sample Variance by Using Microsoft Excel

Science.gov (United States)

Ding, Jian-Hua; Jin, Xian-Wen; Shuai, Ling-Ying

2017-01-01

In this article, the degrees of freedom of the sample variance are simulated by using the Visual Basic for Applications of Microsoft Excel 2010. The simulation file dynamically displays why the sample variance should be calculated by dividing the sum of squared deviations by n-1 rather than n, which is helpful for students to grasp the meaning of…

A generalized Levene's scale test for variance heterogeneity in the presence of sample correlation and group uncertainty.

Science.gov (United States)

Soave, David; Sun, Lei

2017-09-01

We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Global Distributions of Temperature Variances At Different Stratospheric Altitudes From Gps/met Data

Science.gov (United States)

Gavrilov, N. M.; Karpova, N. V.; Jacobi, Ch.

The GPS/MET measurements at altitudes 5 - 35 km are used to obtain global distribu- tions of small-scale temperature variances at different stratospheric altitudes. Individ- ual temperature profiles are smoothed using second order polynomial approximations in 5 - 7 km thick layers centered at 10, 20 and 30 km. Temperature inclinations from the averaged values and their variances obtained for each profile are averaged for each month of year during the GPS/MET experiment. Global distributions of temperature variances have inhomogeneous structure. Locations and latitude distributions of the maxima and minima of the variances depend on altitudes and season. One of the rea- sons for the small-scale temperature perturbations in the stratosphere could be internal gravity waves (IGWs). Some assumptions are made about peculiarities of IGW gener- ation and propagation in the tropo-stratosphere based on the results of GPS/MET data analysis.

Asymptotics of variance of the lattice point count

Czech Academy of Sciences Publication Activity Database

Janáček, Jiří

2008-01-01

Roč. 58, č. 3 (2008), s. 751-758 ISSN 0011-4642 R&D Projects: GA AV ČR(CZ) IAA100110502 Institutional research plan: CEZ:AV0Z50110509 Keywords : point lattice * variance Subject RIV: BA - General Mathematics Impact factor: 0.210, year: 2008

Bounds for Tail Probabilities of the Sample Variance

Directory of Open Access Journals (Sweden)

Van Zuijlen M

2009-01-01

Full Text Available We provide bounds for tail probabilities of the sample variance. The bounds are expressed in terms of Hoeffding functions and are the sharpest known. They are designed having in mind applications in auditing as well as in processing data related to environment.

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed likelihood function, or estimating function, corresponding...

Age Differences in the Variance of Personality Characteristics

Czech Academy of Sciences Publication Activity Database

Mottus, R.; Allik, J.; Hřebíčková, Martina; Kööts-Ausmees, L.; Realo, A.

2016-01-01

Roč. 30, č. 1 (2016), s. 4-11 ISSN 0890-2070 R&D Projects: GA ČR GA13-25656S Institutional support: RVO:68081740 Keywords : variance * individual differences * personality * five-factor model Subject RIV: AN - Psychology Impact factor: 3.707, year: 2016

Adaptation to Variance of Stimuli in Drosophila Larva Navigation

Science.gov (United States)

Wolk, Jason; Gepner, Ruben; Gershow, Marc

In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS

Directory of Open Access Journals (Sweden)

Daniel Menezes Cavalcante

2016-07-01

Full Text Available Portfolio optimization strategies are advocated as being able to allow the composition of stocks portfolios that provide returns above market benchmarks. This study aims to determine whether, in fact, portfolios based on the minimum variance strategy, optimized by the Modern Portfolio Theory, are able to achieve earnings above market benchmarks in Brazil. Time series of 36 securities traded on the BM&FBOVESPA have been analyzed in a long period of time (1999-2012, with sample windows of 12, 36, 60 and 120 monthly observations. The results indicated that the minimum variance portfolio performance is superior to market benchmarks (CDI and IBOVESPA in terms of return and risk-adjusted return, especially in medium and long-term investment horizons.

The value of travel time variance

OpenAIRE

Fosgerau, Mogens; Engelson, Leonid

2010-01-01

This paper considers the value of travel time variability under scheduling preferences that are de�fined in terms of linearly time-varying utility rates associated with being at the origin and at the destination. The main result is a simple expression for the value of travel time variability that does not depend on the shape of the travel time distribution. The related measure of travel time variability is the variance of travel time. These conclusions apply equally to travellers who can free...

Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction

Directory of Open Access Journals (Sweden)

Ling Huang

2017-02-01

Full Text Available Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 1016 electrons/m2 with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the

Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

NARCIS (Netherlands)

Mulder, H.A.; Bijma, P.; Hill, W.G.

2007-01-01

There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework

Modelling Changes in the Unconditional Variance of Long Stock Return Series

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

In this paper we develop a testing and modelling procedure for describing the long-term volatility movements over very long return series. For the purpose, we assume that volatility is multiplicatively decomposed into a conditional and an unconditional component as in Amado and Teräsvirta (2011...... show that the long-memory property in volatility may be explained by ignored changes in the unconditional variance of the long series. Finally, based on a formal statistical test we find evidence of the superiority of volatility forecast accuracy of the new model over the GJR-GARCH model at all...... horizons for a subset of the long return series....

Vertical velocity variances and Reynold stresses at Brookhaven

DEFF Research Database (Denmark)

Busch, Niels E.; Brown, R.M.; Frizzola, J.A.

1970-01-01

Results of wind tunnel tests of the Brookhaven annular bivane are presented. The energy transfer functions describing the instrument response and the numerical filter employed in the data reduction process have been used to obtain corrected values of the normalized variance of the vertical wind v...

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed like- lihood function, or estimating function, corresponding...

The impact of wind generation on the electricity spot-market price level and variance: The Texas experience

International Nuclear Information System (INIS)

Woo, C.K.; Horowitz, I.; Moore, J.; Pacheco, A.

2011-01-01

The literature on renewable energy suggests that an increase in intermittent wind generation would reduce the spot electricity market price by displacing high fuel-cost marginal generation. Taking advantage of a large file of Texas-based 15-min data, we show that while rising wind generation does indeed tend to reduce the level of spot prices, it is also likely to enlarge the spot-price variance. The key policy implication is that increasing use of price risk management should accompany expanded deployment of wind generation. - Highlights: → Rising wind generation in ERCOT tends to reduce electricity spot prices. → Rising wind generation in ERCOT is also likely to enlarge the spot-price variance. → Increased price risk management should accompany expanded wind power deployment.

Time Reversal Migration for Passive Sources Using a Maximum Variance Imaging Condition

KAUST Repository

Wang, H.; Alkhalifah, Tariq Ali

2017-01-01

The conventional time-reversal imaging approach for micro-seismic or passive source location is based on focusing the back-propagated wavefields from each recorded trace in a source image. It suffers from strong background noise and limited acquisition aperture, which may create unexpected artifacts and cause error in the source location. To overcome such a problem, we propose a new imaging condition for microseismic imaging, which is based on comparing the amplitude variance in certain windows, and use it to suppress the artifacts as well as find the right location for passive sources. Instead of simply searching for the maximum energy point in the back-propagated wavefield, we calculate the amplitude variances over a window moving in both space and time axis to create a highly resolved passive event image. The variance operation has negligible cost compared with the forward/backward modeling operations, which reveals that the maximum variance imaging condition is efficient and effective. We test our approach numerically on a simple three-layer model and on a piece of the Marmousi model as well, both of which have shown reasonably good results.

Toward a more robust variance-based global sensitivity analysis of model outputs

Energy Technology Data Exchange (ETDEWEB)

Tong, C

2007-10-15

Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

Time Reversal Migration for Passive Sources Using a Maximum Variance Imaging Condition

KAUST Repository

Wang, H.

2017-05-26

The conventional time-reversal imaging approach for micro-seismic or passive source location is based on focusing the back-propagated wavefields from each recorded trace in a source image. It suffers from strong background noise and limited acquisition aperture, which may create unexpected artifacts and cause error in the source location. To overcome such a problem, we propose a new imaging condition for microseismic imaging, which is based on comparing the amplitude variance in certain windows, and use it to suppress the artifacts as well as find the right location for passive sources. Instead of simply searching for the maximum energy point in the back-propagated wavefield, we calculate the amplitude variances over a window moving in both space and time axis to create a highly resolved passive event image. The variance operation has negligible cost compared with the forward/backward modeling operations, which reveals that the maximum variance imaging condition is efficient and effective. We test our approach numerically on a simple three-layer model and on a piece of the Marmousi model as well, both of which have shown reasonably good results.

Excluded-Mean-Variance Neural Decision Analyzer for Qualitative Group Decision Making

Directory of Open Access Journals (Sweden)

Ki-Young Song

2012-01-01

Full Text Available Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper we introduce an innovative approach to group decision making in uncertain situations by using a mean-variance neural approach. The key idea of this proposed approach is to compute the excluded mean of individual evaluations and weight it by applying a variance influence function (VIF; this process of weighting the excluded mean by VIF provides an improved result in the group decision making. In this paper, a case study with the proposed excluded-mean-variance approach is also presented. The results of this case study indicate that this proposed approach can improve the effectiveness of qualitative decision making by providing the decision maker with a new cognitive tool to assist in the reasoning process.

Estimation variance bounds of importance sampling simulations in digital communication systems

Science.gov (United States)

Lu, D.; Yao, K.

1991-01-01

In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.

Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

Science.gov (United States)

Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

2008-07-01

Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

Heterogeneous network epidemics: real-time growth, variance and extinction of infection.

Science.gov (United States)

Ball, Frank; House, Thomas

2017-09-01

Recent years have seen a large amount of interest in epidemics on networks as a way of representing the complex structure of contacts capable of spreading infections through the modern human population. The configuration model is a popular choice in theoretical studies since it combines the ability to specify the distribution of the number of contacts (degree) with analytical tractability. Here we consider the early real-time behaviour of the Markovian SIR epidemic model on a configuration model network using a multitype branching process. We find closed-form analytic expressions for the mean and variance of the number of infectious individuals as a function of time and the degree of the initially infected individual(s), and write down a system of differential equations for the probability of extinction by time t that are numerically fast compared to Monte Carlo simulation. We show that these quantities are all sensitive to the degree distribution-in particular we confirm that the mean prevalence of infection depends on the first two moments of the degree distribution and the variance in prevalence depends on the first three moments of the degree distribution. In contrast to most existing analytic approaches, the accuracy of these results does not depend on having a large number of infectious individuals, meaning that in the large population limit they would be asymptotically exact even for one initial infectious individual.

On the multiplicity of option prices under CEV with positive elasticity of variance

NARCIS (Netherlands)

Veestraeten, D.

2017-01-01

The discounted stock price under the Constant Elasticity of Variance model is not a martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the price for which put-call parity holds and the price that represents the lowest cost of

On the multiplicity of option prices under CEV with positive elasticity of variance

NARCIS (Netherlands)

Veestraeten, D.

2014-01-01

The discounted stock price under the Constant Elasticity of Variance (CEV) model is a strict local martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the risk-neutral call price and an alternative price that is linked to the unique

The VIX, the Variance Premium, and Expected Returns

DEFF Research Database (Denmark)

Osterrieder, Daniela Maria; Ventosa-Santaulària, Daniel; Vera-Valdés, Eduardo

2018-01-01

. These problems are eliminated if risk is captured by the variance premium (VP) instead; it is unobservable, however. We propose a 2SLS estimator that produces consistent estimates without observing the VP. Using this method, we find a positive risk–return trade-off and long-run return predictability. Our...

Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...

African Journals Online (AJOL)

Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...

Compounding approach for univariate time series with nonstationary variances

Science.gov (United States)

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Robust LOD scores for variance component-based linkage analysis.

Science.gov (United States)

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

A Random Parameter Model for Continuous-Time Mean-Variance Asset-Liability Management

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2015-01-01

Full Text Available We consider a continuous-time mean-variance asset-liability management problem in a market with random market parameters; that is, interest rate, appreciation rates, and volatility rates are considered to be stochastic processes. By using the theories of stochastic linear-quadratic (LQ optimal control and backward stochastic differential equations (BSDEs, we tackle this problem and derive optimal investment strategies as well as the mean-variance efficient frontier analytically in terms of the solution of BSDEs. We find that the efficient frontier is still a parabola in a market with random parameters. Comparing with the existing results, we also find that the liability does not affect the feasibility of the mean-variance portfolio selection problem. However, in an incomplete market with random parameters, the liability can not be fully hedged.

Reduction of treatment delivery variances with a computer-controlled treatment delivery system

International Nuclear Information System (INIS)

Fraass, B.A.; Lash, K.L.; Matrone, G.M.; Lichter, A.S.

1997-01-01

Purpose: To analyze treatment delivery variances for 3-D conformal therapy performed at various levels of treatment delivery automation, ranging from manual field setup to virtually complete computer-controlled treatment delivery using a computer-controlled conformal radiotherapy system. Materials and Methods: All external beam treatments performed in our department during six months of 1996 were analyzed to study treatment delivery variances versus treatment complexity. Treatments for 505 patients (40,641 individual treatment ports) on four treatment machines were studied. All treatment variances noted by treatment therapists or quality assurance reviews (39 in all) were analyzed. Machines 'M1' (CLinac (6(100))) and 'M2' (CLinac 1800) were operated in a standard manual setup mode, with no record and verify system (R/V). Machines 'M3' (CLinac 2100CD/MLC) and ''M4'' (MM50 racetrack microtron system with MLC) treated patients under the control of a computer-controlled conformal radiotherapy system (CCRS) which 1) downloads the treatment delivery plan from the planning system, 2) performs some (or all) of the machine set-up and treatment delivery for each field, 3) monitors treatment delivery, 4) records all treatment parameters, and 5) notes exceptions to the electronically-prescribed plan. Complete external computer control is not available on M3, so it uses as many CCRS features as possible, while M4 operates completely under CCRS control and performs semi-automated and automated multi-segment intensity modulated treatments. Analysis of treatment complexity was based on numbers of fields, individual segments (ports), non-axial and non-coplanar plans, multi-segment intensity modulation, and pseudo-isocentric treatments (and other plans with computer-controlled table motions). Treatment delivery time was obtained from the computerized scheduling system (for manual treatments) or from CCRS system logs. Treatment therapists rotate among the machines, so this analysis

Testing constancy of unconditional variance in volatility models by misspecification and specification tests

DEFF Research Database (Denmark)

Silvennoinen, Annastiina; Terasvirta, Timo

The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH...... models. An application to exchange rate returns is included....

Variance of a potential of mean force obtained using the weighted histogram analysis method.

Science.gov (United States)

Cukier, Robert I

2013-11-27

A potential of mean force (PMF) that provides the free energy of a thermally driven system along some chosen reaction coordinate (RC) is a useful descriptor of systems characterized by complex, high dimensional potential energy surfaces. Umbrella sampling window simulations use potential energy restraints to provide more uniform sampling along a RC so that potential energy barriers that would otherwise make equilibrium sampling computationally difficult can be overcome. Combining the results from the different biased window trajectories can be accomplished using the Weighted Histogram Analysis Method (WHAM). Here, we provide an analysis of the variance of a PMF along the reaction coordinate. We assume that the potential restraints used for each window lead to Gaussian distributions for the window reaction coordinate densities and that the data sampling in each window is from an equilibrium ensemble sampled so that successive points are statistically independent. Also, we assume that neighbor window densities overlap, as required in WHAM, and that further-than-neighbor window density overlap is negligible. Then, an analytic expression for the variance of the PMF along the reaction coordinate at a desired level of spatial resolution can be generated. The variance separates into a sum over all windows with two kinds of contributions: One from the variance of the biased window density normalized by the total biased window density and the other from the variance of the local (for each window's coordinate range) PMF. Based on the desired spatial resolution of the PMF, the former variance can be minimized relative to that from the latter. The method is applied to a model system that has features of a complex energy landscape evocative of a protein with two conformational states separated by a free energy barrier along a collective reaction coordinate. The variance can be constructed from data that is already available from the WHAM PMF construction.

Markov bridges, bisection and variance reduction

DEFF Research Database (Denmark)

Asmussen, Søren; Hobolth, Asger

. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...

The link between response time and preference, variance and processing heterogeneity in stated choice experiments

DEFF Research Database (Denmark)

Campbell, Danny; Mørkbak, Morten Raun; Olsen, Søren Bøye

2018-01-01

In this article we utilize the time respondents require to answer a self-administered online stated preference survey. While the effects of response time have been previously explored, this article proposes a different approach that explicitly recognizes the highly equivocal relationship between ...... between response time and utility coefficients, error variance and processing strategies. Our results thus emphasize the importance of considering response time when modeling stated choice data....... response time and respondents' choices. In particular, we attempt to disentangle preference, variance and processing heterogeneity and explore whether response time helps to explain these three types of heterogeneity. For this, we divide the data (ordered by response time) into approximately equal......-sized subsets, and then derive different class membership probabilities for each subset. We estimate a large number of candidate models and subsequently conduct a frequentist-based model averaging approach using information criteria to derive weights of evidence for each model. Our findings show a clear link...

Mean-Variance Portfolio Selection with Margin Requirements

Directory of Open Access Journals (Sweden)

Yuan Zhou

2013-01-01

Full Text Available We study the continuous-time mean-variance portfolio selection problem in the situation when investors must pay margin for short selling. The problem is essentially a nonlinear stochastic optimal control problem because the coefficients of positive and negative parts of control variables are different. We can not apply the results of stochastic linearquadratic (LQ problem. Also the solution of corresponding Hamilton-Jacobi-Bellman (HJB equation is not smooth. Li et al. (2002 studied the case when short selling is prohibited; therefore they only need to consider the positive part of control variables, whereas we need to handle both the positive part and the negative part of control variables. The main difficulty is that the positive part and the negative part are not independent. The previous results are not directly applicable. By decomposing the problem into several subproblems we figure out the solutions of HJB equation in two disjoint regions and then prove it is the viscosity solution of HJB equation. Finally we formulate solution of optimal portfolio and the efficient frontier. We also present two examples showing how different margin rates affect the optimal solutions and the efficient frontier.

Modeling the subfilter scalar variance for large eddy simulation in forced isotropic turbulence

Science.gov (United States)

Cheminet, Adam; Blanquart, Guillaume

2011-11-01

Static and dynamic model for the subfilter scalar variance in homogeneous isotropic turbulence are investigated using direct numerical simulations (DNS) of a lineary forced passive scalar field. First, we introduce a new scalar forcing technique conditioned only on the scalar field which allows the fluctuating scalar field to reach a statistically stationary state. Statistical properties, including 2nd and 3rd statistical moments, spectra, and probability density functions of the scalar field have been analyzed. Using this technique, we performed constant density and variable density DNS of scalar mixing in isotropic turbulence. The results are used in an a-priori study of scalar variance models. Emphasis is placed on further studying the dynamic model introduced by G. Balarac, H. Pitsch and V. Raman [Phys. Fluids 20, (2008)]. Scalar variance models based on Bedford and Yeo's expansion are accurate for small filter width but errors arise in the inertial subrange. Results suggest that a constant coefficient computed from an assumed Kolmogorov spectrum is often sufficient to predict the subfilter scalar variance.

Isolating Trait and Method Variance in the Measurement of Callous and Unemotional Traits.

Science.gov (United States)

Paiva-Salisbury, Melissa L; Gill, Andrew D; Stickle, Timothy R

2017-09-01

To examine hypothesized influence of method variance from negatively keyed items in measurement of callous-unemotional (CU) traits, nine a priori confirmatory factor analysis model comparisons of the Inventory of Callous-Unemotional Traits were evaluated on multiple fit indices and theoretical coherence. Tested models included a unidimensional model, a three-factor model, a three-bifactor model, an item response theory-shortened model, two item-parceled models, and three correlated trait-correlated method minus one models (unidimensional, correlated three-factor, and bifactor). Data were self-reports of 234 adolescents (191 juvenile offenders, 43 high school students; 63% male; ages 11-17 years). Consistent with hypotheses, models accounting for method variance substantially improved fit to the data. Additionally, bifactor models with a general CU factor better fit the data compared with correlated factor models, suggesting a general CU factor is important to understanding the construct of CU traits. Future Inventory of Callous-Unemotional Traits analyses should account for method variance from item keying and response bias to isolate trait variance.

Genetic factors explain half of all variance in serum eosinophil cationic protein

DEFF Research Database (Denmark)

Elmose, Camilla; Sverrild, Asger; van der Sluis, Sophie

2014-01-01

with variation in serum ECP and to determine the relative proportion of the variation in ECP due to genetic and non-genetic factors, in an adult twin sample. METHODS: A sample of 575 twins, selected through a proband with self-reported asthma, had serum ECP, lung function, airway responsiveness to methacholine......, exhaled nitric oxide, and skin test reactivity, measured. Linear regression analysis and variance component models were used to study factors associated with variation in ECP and the relative genetic influence on ECP levels. RESULTS: Sex (regression coefficient = -0.107, P ... was statistically non-significant (r = -0.11, P = 0.50). CONCLUSION: Around half of all variance in serum ECP is explained by genetic factors. Serum ECP is influenced by sex, BMI, and airway responsiveness. Serum ECP and airway responsiveness seem not to share genetic variance....

Tip displacement variance of manipulator to simultaneous horizontal and vertical stochastic base excitations

International Nuclear Information System (INIS)

Rahi, A.; Bahrami, M.; Rastegar, J.

2002-01-01

The tip displacement variance of an articulated robotic manipulator to simultaneous horizontal and vertical stochastic base excitation is studied. The dynamic equations for an n-links manipulator subjected to both horizontal and vertical stochastic excitations are derived by Lagrangian method and decoupled for small displacement of joints. The dynamic response covariance of the manipulator links is computed in the coordinate frame attached to the base and then the principal variance of tip displacement is determined. Finally, simulation for a two-link planner robotic manipulator under base excitation is developed. Then sensitivity of the principal variance of tip displacement and tip velocity to manipulator configuration, damping, excitation parameters and manipulator links length are investigated

Variance squeezing and entanglement of the XX central spin model

International Nuclear Information System (INIS)

El-Orany, Faisal A A; Abdalla, M Sebawe

2011-01-01

In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.

Variance squeezing and entanglement of the XX central spin model

Energy Technology Data Exchange (ETDEWEB)

El-Orany, Faisal A A [Department of Mathematics and Computer Science, Faculty of Science, Suez Canal University, Ismailia (Egypt); Abdalla, M Sebawe, E-mail: m.sebaweh@physics.org [Mathematics Department, College of Science, King Saud University PO Box 2455, Riyadh 11451 (Saudi Arabia)

2011-01-21

In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.

Estimation of the genetic diversity in tetraploid alfalfa populations based on RAPD markers for breeding purposes.

Science.gov (United States)

Nagl, Nevena; Taski-Ajdukovic, Ksenija; Barac, Goran; Baburski, Aleksandar; Seccareccia, Ivana; Milic, Dragan; Katic, Slobodan

2011-01-01

Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon's information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA) showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.

Estimation of the Genetic Diversity in Tetraploid Alfalfa Populations Based on RAPD Markers for Breeding Purposes

Directory of Open Access Journals (Sweden)

Slobodan Katic

2011-08-01

Full Text Available Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon’s information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.

Improved analysis of all-sky meteor radar measurements of gravity wave variances and momentum fluxes

Directory of Open Access Journals (Sweden)

V. F. Andrioli

2013-05-01

Full Text Available The advantages of using a composite day analysis for all-sky interferometric meteor radars when measuring mean winds and tides are widely known. On the other hand, problems arise if this technique is applied to Hocking's (2005 gravity wave analysis for all-sky meteor radars. In this paper we describe how a simple change in the procedure makes it possible to use a composite day in Hocking's analysis. Also, we explain how a modified composite day can be constructed to test its ability to measure gravity wave momentum fluxes. Test results for specified mean, tidal, and gravity wave fields, including tidal amplitudes and gravity wave momentum fluxes varying strongly with altitude and/or time, suggest that the modified composite day allows characterization of monthly mean profiles of the gravity wave momentum fluxes, with good accuracy at least at the altitudes where the meteor counts are large (from 89 to 92.5 km. In the present work we also show that the variances measured with Hocking's method are often contaminated by the tidal fields and suggest a method of empirical correction derived from a simple simulation model. The results presented here greatly increase our confidence because they show that our technique is able to remove the tide-induced false variances from Hocking's analysis.

Variance of indoor radon concentration: Major influencing factors

Energy Technology Data Exchange (ETDEWEB)

Yarmoshenko, I., E-mail: ivy@ecko.uran.ru [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Vasilyev, A.; Malinovsky, G. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Bossew, P. [German Federal Office for Radiation Protection (BfS), Berlin (Germany); Žunić, Z.S. [Institute of Nuclear Sciences “Vinca”, University of Belgrade (Serbia); Onischenko, A.; Zhukovsky, M. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation)

2016-01-15

Variance of radon concentration in dwelling atmosphere is analysed with regard to geogenic and anthropogenic influencing factors. Analysis includes review of 81 national and regional indoor radon surveys with varying sampling pattern, sample size and duration of measurements and detailed consideration of two regional surveys (Sverdlovsk oblast, Russia and Niška Banja, Serbia). The analysis of the geometric standard deviation revealed that main factors influencing the dispersion of indoor radon concentration over the territory are as follows: area of territory, sample size, characteristics of measurements technique, the radon geogenic potential, building construction characteristics and living habits. As shown for Sverdlovsk oblast and Niška Banja town the dispersion as quantified by GSD is reduced by restricting to certain levels of control factors. Application of the developed approach to characterization of the world population radon exposure is discussed. - Highlights: • Influence of lithosphere and anthroposphere on variance of indoor radon is found. • Level-by-level analysis reduces GSD by a factor of 1.9. • Worldwide GSD is underestimated.

Mean-Variance-Validation Technique for Sequential Kriging Metamodels

International Nuclear Information System (INIS)

Lee, Tae Hee; Kim, Ho Sung

2010-01-01

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean 0 validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean 0 validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels

The Theory of Variances in Equilibrium Reconstruction

International Nuclear Information System (INIS)

Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren

2008-01-01

The theory of variances of equilibrium reconstruction is presented. It complements existing practices with information regarding what kind of plasma profiles can be reconstructed, how accurately, and what remains beyond the abilities of diagnostic systems. The σ-curves, introduced by the present theory, give a quantitative assessment of quality of effectiveness of diagnostic systems in constraining equilibrium reconstructions. The theory also suggests a method for aligning the accuracy of measurements of different physical nature

Introduction to variance estimation

CERN Document Server

Wolter, Kirk M

2007-01-01

We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully. The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who...

Is fMRI ?noise? really noise? Resting state nuisance regressors remove variance with network structure

OpenAIRE

Bright, Molly G.; Murphy, Kevin

2015-01-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed ...

Risk implications of renewable support instruments: Comparative analysis of feed-in tariffs and premiums using a mean-variance approach

DEFF Research Database (Denmark)

Kitzing, Lena

2014-01-01

. Using cash flow analysis, Monte Carlo simulations and mean-variance analysis, we quantify risk-return relationships for an exemplary offshore wind park in a simplified setting. We show that feedin tariffs systematically require lower direct support levels than feed-in premiums while providing the same...

On zero variance Monte Carlo path-stretching schemes

International Nuclear Information System (INIS)

Lux, I.

1983-01-01

A zero variance path-stretching biasing scheme proposed for a special case by Dwivedi is derived in full generality. The procedure turns out to be the generalization of the exponential transform. It is shown that the biased game can be interpreted as an analog simulation procedure, thus saving some computational effort in comparison with the corresponding nonanalog game

Variances as order parameter and complexity measure for random Boolean networks

International Nuclear Information System (INIS)

Luque, Bartolo; Ballesteros, Fernando J; Fernandez, Manuel

2005-01-01

Several order parameters have been considered to predict and characterize the transition between ordered and disordered phases in random Boolean networks, such as the Hamming distance between replicas or the stable core, which have been successfully used. In this work, we propose a natural and clear new order parameter: the temporal variance. We compute its value analytically and compare it with the results of numerical experiments. Finally, we propose a complexity measure based on the compromise between temporal and spatial variances. This new order parameter and its related complexity measure can be easily applied to other complex systems

Variances as order parameter and complexity measure for random Boolean networks

Energy Technology Data Exchange (ETDEWEB)

Luque, Bartolo [Departamento de Matematica Aplicada y EstadIstica, Escuela Superior de Ingenieros Aeronauticos, Universidad Politecnica de Madrid, Plaza Cardenal Cisneros 3, Madrid 28040 (Spain); Ballesteros, Fernando J [Observatori Astronomic, Universitat de Valencia, Ed. Instituts d' Investigacio, Pol. La Coma s/n, E-46980 Paterna, Valencia (Spain); Fernandez, Manuel [Departamento de Matematica Aplicada y EstadIstica, Escuela Superior de Ingenieros Aeronauticos, Universidad Politecnica de Madrid, Plaza Cardenal Cisneros 3, Madrid 28040 (Spain)

2005-02-04

Several order parameters have been considered to predict and characterize the transition between ordered and disordered phases in random Boolean networks, such as the Hamming distance between replicas or the stable core, which have been successfully used. In this work, we propose a natural and clear new order parameter: the temporal variance. We compute its value analytically and compare it with the results of numerical experiments. Finally, we propose a complexity measure based on the compromise between temporal and spatial variances. This new order parameter and its related complexity measure can be easily applied to other complex systems.

Variance-optimal hedging for processes with stationary independent increments

DEFF Research Database (Denmark)

Hubalek, Friedrich; Kallsen, J.; Krawczyk, L.

We determine the variance-optimal hedge when the logarithm of the underlying price follows a process with stationary independent increments in discrete or continuous time. Although the general solution to this problem is known as backward recursion or backward stochastic differential equation, we...

The variance quadtree algorithm: use for spatial sampling design

NARCIS (Netherlands)

Minasny, B.; McBratney, A.B.; Walvoort, D.J.J.

2007-01-01

Spatial sampling schemes are mainly developed to determine sampling locations that can cover the variation of environmental properties in the area of interest. Here we proposed the variance quadtree algorithm for sampling in an area with prior information represented as ancillary or secondary

A mean-variance frontier in discrete and continuous time

NARCIS (Netherlands)

Bekker, Paul A.

2004-01-01

The paper presents a mean-variance frontier based on dynamic frictionless investment strategies in continuous time. The result applies to a finite number of risky assets whose price process is given by multivariate geometric Brownian motion with deterministically varying coefficients. The derivation

Investor preferences for oil spot and futures based on mean-variance and stochastic dominance

NARCIS (Netherlands)

H.H. Lean (Hooi Hooi); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)

2010-01-01

textabstractThis paper examines investor preferences for oil spot and futures based on mean-variance (MV) and stochastic dominance (SD). The mean-variance criterion cannot distinct the preferences of spot and market whereas SD tests leads to the conclusion that spot dominates futures in the downside

Impact of time-inhomogeneous jumps and leverage type effects on returns and realised variances

DEFF Research Database (Denmark)

Veraart, Almut

This paper studies the effect of time-inhomogeneous jumps and leverage type effects on realised variance calculations when the logarithmic asset price is given by a Lévy-driven stochastic volatility model. In such a model, the realised variance is an inconsistent estimator of the integrated...

Historical explanation of genetic variation in the Mediterranean horseshoe bat Rhinolophus euryale (Chiroptera: Rhinolophidae) inferred from mitochondrial cytochrome-b and D-loop genes in Iran.

Science.gov (United States)

Najafi, Nargess; Akmali, Vahid; Sharifi, Mozafar

2018-04-26

Molecular phylogeography and species distribution modelling (SDM) suggest that late Quaternary glacial cycles have portrayed a significant role in structuring current population genetic structure and diversity. Based on phylogenetic relationships using Bayesian inference and maximum likelihood of 535 bp mtDNA (D-loop) and 745 bp mtDNA (Cytb) in 62 individuals of the Mediterranean Horseshoe Bat, Rhinolophus euryale, from 13 different localities in Iran we identified two subspecific populations with differing population genetic structure distributed in southern Zagros Mts. and northern Elburz Mts. Analysis of molecular variance (AMOVA) obtained from D-loop sequences indicates that 21.18% of sequence variation is distributed among populations and 10.84% within them. Moreover, a degree of genetic subdivision, mainly attributable to the existence of significant variance among the two regions is shown (θCT = 0.68, p = .005). The positive and significant correlation between geographic and genetic distances (R 2  = 0.28, r = 0.529, p = .000) is obtained following controlling for environmental distance. Spatial distribution of haplotypes indicates that marginal population of the species in southern part of the species range have occupied this section as a glacial refugia. However, this genetic variation, in conjunction with results of the SDM shows a massive postglacial range expansion for R. euryale towards higher latitudes in Iran.

Population genetics of Thamnaconus hypargyreus (Tetraodontiformes: Monacanthidae) in the South China Sea.

Science.gov (United States)

Li, Yufang; Chen, Guobao; Yu, Jie; Wu, Shuiqing; Xiong, Dan; Li, Xia; Cui, Ke; Li, Yongzhen

2016-01-01

Knowledge of population structure is particularly important for long-term fisheries management and conservation. Lesser-spotted leatherjacket Thamnaconus hypargyreus is an economically important fish species in the South China Sea. Fish specimens (totally 158 individuals) used in this study were collected from five geographical locations in the north of the South China Sea and the southwestern Nansha Islands. The results were as follows: a total of 636 nucleotides of the mitochondrial DNA (mtDNA) control region (CR) of T. hypargyreus were amplified by polymerase chain reaction (PCR) technology. Both 103 mutations of nucleotide acids without inserting or deleting one and 91 haplotypes were found among the examined CR fragment. High haplotype diversity (0.9419 ± 0.0151) and nucleotide diversity (0.0095 ± 0.00506) relatively together with a recent and sudden population expansion which characterizes the genetic population structure of this species. Analysis of molecular variance (AMOVA) and the fixation indices (Fst) of five groups showed that the genetic variance mainly came from individuals within groups, and there was no genetic differentiation between groups. The phylogenetic trees including maximum likelihood (ML) and Bayesian inference (BI) proved no phylogeographic differentiation structure in five groups. The mtDNA marker suggested the five groups should be genetic homogeneity, which implied T. hypargyreus in the north and southwest continental shelf of the South China Sea belongs to one population.

Comment on Hoffman and Rovine (2007): SPSS MIXED can estimate models with heterogeneous variances.

Science.gov (United States)

Weaver, Bruce; Black, Ryan A

2015-06-01

Hoffman and Rovine (Behavior Research Methods, 39:101-117, 2007) have provided a very nice overview of how multilevel models can be useful to experimental psychologists. They included two illustrative examples and provided both SAS and SPSS commands for estimating the models they reported. However, upon examining the SPSS syntax for the models reported in their Table 3, we found no syntax for models 2B and 3B, both of which have heterogeneous error variances. Instead, there is syntax that estimates similar models with homogeneous error variances and a comment stating that SPSS does not allow heterogeneous errors. But that is not correct. We provide SPSS MIXED commands to estimate models 2B and 3B with heterogeneous error variances and obtain results nearly identical to those reported by Hoffman and Rovine in their Table 3. Therefore, contrary to the comment in Hoffman and Rovine's syntax file, SPSS MIXED can estimate models with heterogeneous error variances.

A log-sinh transformation for data normalization and variance stabilization

Science.gov (United States)

Wang, Q. J.; Shrestha, D. L.; Robertson, D. E.; Pokhrel, P.

2012-05-01

When quantifying model prediction uncertainty, it is statistically convenient to represent model errors that are normally distributed with a constant variance. The Box-Cox transformation is the most widely used technique to normalize data and stabilize variance, but it is not without limitations. In this paper, a log-sinh transformation is derived based on a pattern of errors commonly seen in hydrological model predictions. It is suited to applications where prediction variables are positively skewed and the spread of errors is seen to first increase rapidly, then slowly, and eventually approach a constant as the prediction variable becomes greater. The log-sinh transformation is applied in two case studies, and the results are compared with one- and two-parameter Box-Cox transformations.

School Audits and School Improvement: Exploring the Variance Point Concept in Kentucky's... Schools

Directory of Open Access Journals (Sweden)

Robert Lyons

2011-01-01

Full Text Available As a diagnostic intervention (Bowles, Churchill, Effrat, & McDermott, 2002 for schools failing to meet school improvement goals, Ken-tucky used a scholastic audit process based on nine standards and 88 associated indicators called the Standards and Indicators for School Improvement (SISI. Schools are rated on a scale of 1–4 on each indicator, with a score of 3 considered as fully functional (Kentucky De-partment of Education [KDE], 2002. As part of enacting the legislation, KDE was required to also audit a random sample of schools that did meet school improvement goals; thereby identifying practices present in improving schools that are not present in those failing to improve. These practices were referred to as variance points, and were reported to school leaders annually. Variance points have differed from year to year, and the methodology used by KDE was unclear. Moreover, variance points were reported for all schools without differentiating based upon the level of school (elementary, middle, or high. In this study, we established a transparent methodology for variance point determination that differentiates between elementary, middle, and high schools.

Kalman filtering techniques for reducing variance of digital speckle displacement measurement noise

Institute of Scientific and Technical Information of China (English)

Donghui Li; Li Guo

2006-01-01

@@ Target dynamics are assumed to be known in measuring digital speckle displacement. Use is made of a simple measurement equation, where measurement noise represents the effect of disturbances introduced in measurement process. From these assumptions, Kalman filter can be designed to reduce variance of measurement noise. An optical and analysis system was set up, by which object motion with constant displacement and constant velocity is experimented with to verify validity of Kalman filtering techniques for reduction of measurement noise variance.

Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes

OpenAIRE

Hoejgaard, B.; Vigna, E.

2007-01-01

We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean-variance approach is then compared to other investment strategies adopted in DC pension schemes, namely the target-based approach and the lifestyle strategy. The comparison is done both in a theoretical...

Bobtail: A Proof-of-Work Target that Minimizes Blockchain Mining Variance (Draft)

OpenAIRE

Bissias, George; Levine, Brian Neil

2017-01-01

Blockchain systems are designed to produce blocks at a constant average rate. The most popular systems currently employ a Proof of Work (PoW) algorithm as a means of creating these blocks. Bitcoin produces, on average, one block every 10 minutes. An unfortunate limitation of all deployed PoW blockchain systems is that the time between blocks has high variance. For example, 5% of the time, Bitcoin's inter-block time is at least 40 minutes. This variance impedes the consistent flow of validated...

Multidimensional adaptive testing with a minimum error-variance criterion

NARCIS (Netherlands)

van der Linden, Willem J.

1997-01-01

The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple

Feynman variance-to-mean in the context of passive neutron coincidence counting

Energy Technology Data Exchange (ETDEWEB)

Croft, S., E-mail: scroft@lanl.gov [Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545 (United States); Favalli, A.; Hauck, D.K.; Henzlova, D.; Santi, P.A. [Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545 (United States)

2012-09-11

Passive Neutron Coincidence Counting (PNCC) based on shift register autocorrelation time analysis of the detected neutron pulse train is an important Nondestructive Assay (NDA) method. It is used extensively in the quantification of plutonium and other spontaneously fissile materials for purposes of nuclear materials accountancy. In addition to the totals count rate, which is also referred to as the singles, gross or trigger rate, a quantity known as the reals coincidence rate, also called the pairs or doubles, is obtained from the difference between the measured neutron multiplicities in two measurement gates triggered by the incoming events on the pulse train. The reals rate is a measure of the number of time correlated pairs present on the pulse train and this can be related to the fission rates (and hence material mass) since fissions emit neutrons in bursts which are also detected in characteristic clusters. A closely related measurement objective is the determination of the reactivity of systems as they approach criticality. In this field an alternative autocorrelation signature is popular, the so called Feynman variance-to-mean technique which makes use of the multiplicity histogram formed the periodic, or clock-triggered opening of a coincidence gate. Workers in these two application areas share common challenges and improvement opportunities but are often separated by tradition, problem focus and technical language. The purpose of this paper is to recognize the close link between the Feynman variance-to-mean metric and traditional PNCC using shift register logic applied to correlated pulse trains. We, show using relationships for the late-gate (or accidentals) histogram recorded using a multiplicity shift register, how the Feynman Y-statistic, defined as the excess variance-to-mean ratio, can be expressed in terms of the singles and doubles rates familiar to the safeguards and waste assay communities. These two specialisms now have a direct bridge between

Efficient Scores, Variance Decompositions and Monte Carlo Swindles.

Science.gov (United States)

1984-08-28

to ;r Then a version .of Pythagoras ’ theorem gives the variance decomposition (6.1) varT var S var o(T-S) P P0 0 0 One way to see this is to note...complete sufficient statistics for (B, a) , and that the standard- ized residuals a(y - XB) 6 are ancillary. Basu’s sufficiency- ancillarity theorem

Genomic selection of crossing partners on basis of the expected mean and variance of their derived lines.

Science.gov (United States)

Osthushenrich, Tanja; Frisch, Matthias; Herzog, Eva

2017-01-01

In a line or a hybrid breeding program superior lines are selected from a breeding pool as parental lines for the next breeding cycle. From a cross of two parental lines, new lines are derived by single-seed descent (SSD) or doubled haploid (DH) technology. However, not all possible crosses between the parental lines can be carried out due to limited resources. Our objectives were to present formulas to characterize a cross by the mean and variance of the genotypic values of the lines derived from the cross, and to apply the formulas to predict means and variances of flowering time traits in recombinant inbred line families of a publicly available data set in maize. We derived formulas which are based on the expected linkage disequilibrium (LD) between two loci and which can be used for arbitrary mating systems. Results were worked out for SSD and DH lines derived from a cross after an arbitrary number of intermating generations. The means and variances were highly correlated with results obtained by the simulation software PopVar. Compared with these simulations, computation time for our closed formulas was about ten times faster. The means and variances for flowering time traits observed in the recombinant inbred line families of the investigated data set showed correlations of around 0.9 for the means and of 0.46 and 0.65 for the standard deviations with the estimated values. We conclude that our results provide a framework that can be exploited to increase the efficiency of hybrid and line breeding programs by extending genomic selection approaches to the selection of crossing partners.

Genomic selection of crossing partners on basis of the expected mean and variance of their derived lines

Science.gov (United States)

Osthushenrich, Tanja; Frisch, Matthias

2017-01-01

In a line or a hybrid breeding program superior lines are selected from a breeding pool as parental lines for the next breeding cycle. From a cross of two parental lines, new lines are derived by single-seed descent (SSD) or doubled haploid (DH) technology. However, not all possible crosses between the parental lines can be carried out due to limited resources. Our objectives were to present formulas to characterize a cross by the mean and variance of the genotypic values of the lines derived from the cross, and to apply the formulas to predict means and variances of flowering time traits in recombinant inbred line families of a publicly available data set in maize. We derived formulas which are based on the expected linkage disequilibrium (LD) between two loci and which can be used for arbitrary mating systems. Results were worked out for SSD and DH lines derived from a cross after an arbitrary number of intermating generations. The means and variances were highly correlated with results obtained by the simulation software PopVar. Compared with these simulations, computation time for our closed formulas was about ten times faster. The means and variances for flowering time traits observed in the recombinant inbred line families of the investigated data set showed correlations of around 0.9 for the means and of 0.46 and 0.65 for the standard deviations with the estimated values. We conclude that our results provide a framework that can be exploited to increase the efficiency of hybrid and line breeding programs by extending genomic selection approaches to the selection of crossing partners. PMID:29200436

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.jp; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo, Kyoto 606-8507 (Japan)

2016-09-15

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

International Nuclear Information System (INIS)

Matsuo, Yukinori; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro

2016-01-01

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

A spatial mean-variance MIP model for energy market risk analysis

International Nuclear Information System (INIS)

Yu, Zuwei

2003-01-01

The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets

A spatial mean-variance MIP model for energy market risk analysis

International Nuclear Information System (INIS)

Zuwei Yu

2003-01-01

The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

A spatial mean-variance MIP model for energy market risk analysis

Energy Technology Data Exchange (ETDEWEB)

Zuwei Yu [Purdue University, West Lafayette, IN (United States). Indiana State Utility Forecasting Group and School of Industrial Engineering

2003-05-01

The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

A spatial mean-variance MIP model for energy market risk analysis

Energy Technology Data Exchange (ETDEWEB)

Yu, Zuwei [Indiana State Utility Forecasting Group and School of Industrial Engineering, Purdue University, Room 334, 1293 A.A. Potter, West Lafayette, IN 47907 (United States)

2003-05-01

The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets.

Portfolios dominating indices: Optimization with second-order stochastic dominance constraints vs. minimum and mean variance portfolios

OpenAIRE

Keçeci, Neslihan Fidan; Kuzmenko, Viktor; Uryasev, Stan

2016-01-01

The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

OpenAIRE

Neslihan Fidan Keçeci; Viktor Kuzmenko; Stan Uryasev

2016-01-01

The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

Genetic variance components for residual feed intake and feed ...

African Journals Online (AJOL)

Feeding costs of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce feeding cost in beef cattle and thereby improve profitability. This study estimated genetic (co)variances between weaning weight and other production, reproduction ...

Cumulative Prospect Theory, Option Returns, and the Variance Premium

NARCIS (Netherlands)

Baele, Lieven; Driessen, Joost; Ebert, Sebastian; Londono Yarce, J.M.; Spalt, Oliver

The variance premium and the pricing of out-of-the-money (OTM) equity index options are major challenges to standard asset pricing models. We develop a tractable equilibrium model with Cumulative Prospect Theory (CPT) preferences that can overcome both challenges. The key insight is that the

Estimates of variance components for postweaning feed intake and ...

African Journals Online (AJOL)

Mike

2013-03-09

Mar 9, 2013 ... transformation of RFIp and RDGp to z-scores (mean = 0.0, variance = 1.0) and then ... generation pedigree (n = 9 653) used for this analysis. ..... Nkrumah, J.D., Basarab, J.A., Wang, Z., Li, C., Price, M.A., Okine, E.K., Crews Jr., ...

Mean-variance portfolio optimization with state-dependent risk aversion

DEFF Research Database (Denmark)

Bjoerk, Tomas; Murgoci, Agatha; Zhou, Xun Yu

2014-01-01

The objective of this paper is to study the mean-variance portfolio optimization in continuous time. Since this problem is time inconsistent we attack it by placing the problem within a game theoretic framework and look for subgame perfect Nash equilibrium strategies. This particular problem has...

Application of effective variance method for contamination monitor calibration

International Nuclear Information System (INIS)

Goncalez, O.L.; Freitas, I.S.M. de.

1990-01-01

In this report, the calibration of a thin window Geiger-Muller type monitor for alpha superficial contamination is presented. The calibration curve is obtained by the method of the least-squares fitting with effective variance. The method and the approach for the calculation are briefly discussed. (author)

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

Science.gov (United States)

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

Minimal variance hedging of natural gas derivatives in exponential Lévy models: Theory and empirical performance

International Nuclear Information System (INIS)

Ewald, Christian-Oliver; Nawar, Roy; Siu, Tak Kuen

2013-01-01

We consider the problem of hedging European options written on natural gas futures, in a market where prices of traded assets exhibit jumps, by trading in the underlying asset. We provide a general expression for the hedging strategy which minimizes the variance of the terminal hedging error, in terms of stochastic integral representations of the payoffs of the options involved. This formula is then applied to compute hedge ratios for common options in various models with jumps, leading to easily computable expressions. As a benchmark we take the standard Black–Scholes and Merton delta hedges. We show that in natural gas option markets minimal variance hedging with underlying consistently outperform the benchmarks by quite a margin. - Highlights: ► We derive hedging strategies for European type options written on natural gas futures. ► These are tested empirically using Henry Hub natural gas futures and options data. ► We find that our hedges systematically outperform classical benchmarks

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

Science.gov (United States)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the

Batch variation between branchial cell cultures: An analysis of variance

DEFF Research Database (Denmark)

Hansen, Heinz Johs. Max; Grosell, M.; Kristensen, L.

2003-01-01

We present in detail how a statistical analysis of variance (ANOVA) is used to sort out the effect of an unexpected batch-to-batch variation between cell cultures. Two separate cultures of rainbow trout branchial cells were grown on permeable filtersupports ("inserts"). They were supposed...... and introducing the observed difference between batches as one of the factors in an expanded three-dimensional ANOVA, we were able to overcome an otherwisecrucial lack of sufficiently reproducible duplicate values. We could thereby show that the effect of changing the apical medium was much more marked when...... the radioactive lipid precursors were added on the apical, rather than on the basolateral, side. Theinsert cell cultures were obviously polarized. We argue that it is not reasonable to reject troublesome experimental results, when we do not know a priori that something went wrong. The ANOVA is a very useful...

An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

Science.gov (United States)

Attali, Yigal

2010-01-01

Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

Directory of Open Access Journals (Sweden)

Zdravko Kačič

2009-01-01

Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

Science.gov (United States)

Kos, Marko; Grašič, Matej; Kačič, Zdravko

2009-12-01

This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

Assessment of genetic diversity using RAPD analysis in a germplasm collection of sea buckthorn

Directory of Open Access Journals (Sweden)

G.I. BARTISH

2008-12-01

Full Text Available Random amplified polymorphic DNA (RAPD markers were used to characterize a part of a sea buckthorn gene bank collected for plant breeding purposes. Molecular markers were generated in 55 cultivars and accessions, representing five subspecies of Hippophae rhamnoides L. and intraspecific hybrids between different subspecies. Sixty-three markers were used to generate a Dice's similarity coefficient matrix of pairwise comparisons between individual RAPD profiles. Cluster (UPGMA and principal co-ordinate analyses, based on this matrix, revealed clustering of plants into groups which generally correspond to their taxonomic classification or geographic origin. The analysis of molecular variance (AMOVA was found useful for estimating components of genetic variation between and within taxonomic and geographic groups of accessions and cultivars. Whereas both alternatives for grouping the material (taxonomic or geographic origin resulted in significant between-group variation, the major part of molecular variance (approximately 75% was still attributed to variation within groups. We conclude that the RAPD analysis is useful for clarification of taxonomic and geographic origin of accessions and cultivars of sea buckthorn.

Waste Isolation Pilot Plant no-migration variance petition

International Nuclear Information System (INIS)

1990-01-01

Section 3004 of RCRA allows EPA to grant a variance from the land disposal restrictions when a demonstration can be made that, to a reasonable degree of certainty, there will be no migration of hazardous constituents from the disposal unit for as long as the waste remains hazardous. Specific requirements for making this demonstration are found in 40 CFR 268.6, and EPA has published a draft guidance document to assist petitioners in preparing a variance request. Throughout the course of preparing this petition, technical staff from DOE, EPA, and their contractors have met frequently to discuss and attempt to resolve issues specific to radioactive mixed waste and the WIPP facility. The DOE believes it meets or exceeds all requirements set forth for making a successful ''no-migration'' demonstration. The petition presents information under five general headings: (1) waste information; (2) site characterization; (3) facility information; (4) assessment of environmental impacts, including the results of waste mobility modeling; and (5) analysis of uncertainties. Additional background and supporting documentation is contained in the 15 appendices to the petition, as well as in an extensive addendum published in October 1989

DFT-based channel estimation and noise variance estimation techniques for single-carrier FDMA

OpenAIRE

Huang, G; Nix, AR; Armour, SMD

2010-01-01

Practical frequency domain equalization (FDE) systems generally require knowledge of the channel and the noise variance to equalize the received signal in a frequency-selective fading channel. Accurate channel estimate and noise variance estimate are thus desirable to improve receiver performance. In this paper we investigate the performance of the denoise channel estimator and the approximate linear minimum mean square error (A-LMMSE) channel estimator with channel power delay profile (PDP) ...

What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.

Science.gov (United States)

de Haan-Rietdijk, Silvia; Kuppens, Peter; Hamaker, Ellen L

2016-01-01

In recent years there has been a growing interest in the use of intensive longitudinal research designs to study within-person processes. Examples are studies that use experience sampling data and autoregressive modeling to investigate emotion dynamics and between-person differences therein. Such designs often involve multiple measurements per day and multiple days per person, and it is not clear how this nesting of the data should be accounted for: That is, should such data be considered as two-level data (which is common practice at this point), with occasions nested in persons, or as three-level data with beeps nested in days which are nested in persons. We show that a significance test of the day-level variance in an empty three-level model is not reliable when there is autocorrelation. Furthermore, we show that misspecifying the number of levels can lead to spurious or misleading findings, such as inflated variance or autoregression estimates. Throughout the paper we present instructions and R code for the implementation of the proposed models, which includes a novel three-level AR(1) model that estimates moment-to-moment inertia and day-to-day inertia. Based on our simulations we recommend model selection using autoregressive multilevel models in combination with the AIC. We illustrate this method using empirical emotion data from two independent samples, and discuss the implications and the relevance of the existence of a day level for the field.

A proxy for variance in dense matching over homogeneous terrain

Science.gov (United States)

Altena, Bas; Cockx, Liesbet; Goedemé, Toon

2014-05-01

Automation in photogrammetry and avionics have brought highly autonomous UAV mapping solutions on the market. These systems have great potential for geophysical research, due to their mobility and simplicity of work. Flight planning can be done on site and orientation parameters are estimated automatically. However, one major drawback is still present: if contrast is lacking, stereoscopy fails. Consequently, topographic information cannot be obtained precisely through photogrammetry for areas with low contrast. Even though more robustness is added in the estimation through multi-view geometry, a precise product is still lacking. For the greater part, interpolation is applied over these regions, where the estimation is constrained by uniqueness, its epipolar line and smoothness. Consequently, digital surface models are generated with an estimate of the topography, without holes but also without an indication of its variance. Every dense matching algorithm is based on a similarity measure. Our methodology uses this property to support the idea that if only noise is present, no correspondence can be detected. Therefore, the noise level is estimated in respect to the intensity signal of the topography (SNR) and this ratio serves as a quality indicator for the automatically generated product. To demonstrate this variance indicator, two different case studies were elaborated. The first study is situated at an open sand mine near the village of Kiezegem, Belgium. Two different UAV systems flew over the site. One system had automatic intensity regulation, and resulted in low contrast over the sandy interior of the mine. That dataset was used to identify the weak estimations of the topography and was compared with the data from the other UAV flight. In the second study a flight campaign with the X100 system was conducted along the coast near Wenduine, Belgium. The obtained images were processed through structure-from-motion software. Although the beach had a very low

Genetic diversity of the Northern Morocco goat population assessed with microsatellite markers

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Najat El Moutchou

2017-12-01

Full Text Available The main goal of this work was to study the genetic diversity of the Northern Morocco goat population through the analysis of 19 microsatellites in 144 animals from 61 herds. To detect a possible population structure, three distinct geographic subpopulations were characterized as a function of climate and environmental influences. Most of the markers were highly polymorphic, and the results revealed considerable genetic variation across the studied loci. A total of 204 alleles were detected, with an average number of 10.7 per locus. The PIC average was 0.728, and four microsatellites showed a significant deviation (p< 0.05 from Hardy-Weinberg Equilibrium. Analysis of molecular variance (AMOVA indicated that only 0.5% of the variation corresponded to differences among subpopulations, and 99.5% corresponded to differences among individuals. Factorial correspondence analysis showed intense admixtures across the putative subpopulations, and the subdivision related to geographical or environmental adaptation was undetectable. The Northern Morocco goat population presented high genetic diversity and a lack of population structure. The main reason for these findings is the absence of the breed concept (reproductively closed population, resulting in uncontrolled crossbreeding with exotic breeds and other local goats.

Genetic diversity of the Northern Morocco goat population assessed with microsatellite markers

Energy Technology Data Exchange (ETDEWEB)

El Moutchou, N.; González-Martínez, A.M.; Chentouf, M.; Lairini, K.; Rodero, E.

2017-07-01

The main goal of this work was to study the genetic diversity of the Northern Morocco goat population through the analysis of 19 microsatellites in 144 animals from 61 herds. To detect a possible population structure, three distinct geographic subpopulations were characterized as a function of climate and environmental influences. Most of the markers were highly polymorphic, and the results revealed considerable genetic variation across the studied loci. A total of 204 alleles were detected, with an average number of 10.7 per locus. The PIC average was 0.728, and four microsatellites showed a significant deviation (p< 0.05) from Hardy-Weinberg Equilibrium. Analysis of molecular variance (AMOVA) indicated that only 0.5% of the variation corresponded to differences among subpopulations, and 99.5% corresponded to differences among individuals. Factorial correspondence analysis showed intense admixtures across the putative subpopulations, and the subdivision related to geographical or environmental adaptation was undetectable. The Northern Morocco goat population presented high genetic diversity and a lack of population structure. The main reason for these findings is the absence of the breed concept (reproductively closed population), resulting in uncontrolled crossbreeding with exotic breeds and other local goats.

Genetic diversity of the Northern Morocco goat population assessed with microsatellite markers

International Nuclear Information System (INIS)

El Moutchou, N.; González-Martínez, A.M.; Chentouf, M.; Lairini, K.; Rodero, E.

2017-01-01

The main goal of this work was to study the genetic diversity of the Northern Morocco goat population through the analysis of 19 microsatellites in 144 animals from 61 herds. To detect a possible population structure, three distinct geographic subpopulations were characterized as a function of climate and environmental influences. Most of the markers were highly polymorphic, and the results revealed considerable genetic variation across the studied loci. A total of 204 alleles were detected, with an average number of 10.7 per locus. The PIC average was 0.728, and four microsatellites showed a significant deviation (p< 0.05) from Hardy-Weinberg Equilibrium. Analysis of molecular variance (AMOVA) indicated that only 0.5% of the variation corresponded to differences among subpopulations, and 99.5% corresponded to differences among individuals. Factorial correspondence analysis showed intense admixtures across the putative subpopulations, and the subdivision related to geographical or environmental adaptation was undetectable. The Northern Morocco goat population presented high genetic diversity and a lack of population structure. The main reason for these findings is the absence of the breed concept (reproductively closed population), resulting in uncontrolled crossbreeding with exotic breeds and other local goats.

Spatio-temporal variance and meteorological drivers of the urban heat island in a European city

Science.gov (United States)

Arnds, Daniela; Böhner, Jürgen; Bechtel, Benjamin

2017-04-01

Urban areas are especially vulnerable to high temperatures, which will intensify in the future due to climate change. Therefore, both good knowledge about the local urban climate as well as simple and robust methods for its projection are needed. This study has analysed the spatio-temporal variance of the mean nocturnal urban heat island (UHI) of Hamburg, with observations from 40 stations from different suppliers. The UHI showed a radial gradient with about 2 K in the centre mostly corresponding to the urban densities. Temporarily, it has a strong seasonal cycle with the highest values between April and September and an inter-annual variability of approximately 0.5 K. Further, synoptic meteorological drivers of the UHI were analysed, which generally is most pronounced under calm and cloud-free conditions. Considered were meteorological parameters such as relative humidity, wind speed, cloud cover and objective weather types. For the stations with the highest UHI intensities, up to 68.7 % of the variance could be explained by seasonal empirical models and even up to 76.6 % by monthly models.

Molecular variance of the Tunisian almond germplasm assessed by ...

African Journals Online (AJOL)

The genetic variance analysis of 82 almond (Prunus dulcis Mill.) genotypes was performed using ten genomic simple sequence repeats (SSRs). A total of 50 genotypes from Tunisia including local landraces identified while prospecting the different sites of Bizerte and Sidi Bouzid (Northern and central parts) which are the ...

Assessment of texture stationarity using the asymptotic behavior of the empirical mean and variance.

Science.gov (United States)

Blanc, Rémy; Da Costa, Jean-Pierre; Stitou, Youssef; Baylou, Pierre; Germain, Christian

2008-09-01

Given textured images considered as realizations of 2-D stochastic processes, a framework is proposed to evaluate the stationarity of their mean and variance. Existing strategies focus on the asymptotic behavior of the empirical mean and variance (respectively EM and EV), known for some types of nondeterministic processes. In this paper, the theoretical asymptotic behaviors of the EM and EV are studied for large classes of second-order stationary ergodic processes, in the sense of the Wold decomposition scheme, including harmonic and evanescent processes. Minimal rates of convergence for the EM and the EV are derived for these processes; they are used as criteria for assessing the stationarity of textures. The experimental estimation of the rate of convergence is achieved using a nonparametric block sub-sampling method. Our framework is evaluated on synthetic processes with stationary or nonstationary mean and variance and on real textures. It is shown that anomalies in the asymptotic behavior of the empirical estimators allow detecting nonstationarities of the mean and variance of the processes in an objective way.

Automatic variance reduction for Monte Carlo simulations via the local importance function transform

International Nuclear Information System (INIS)

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ''real'' particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ''black box''. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases

On mean reward variance in semi-Markov processes

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2005-01-01

Roč. 62, č. 3 (2005), s. 387-397 ISSN 1432-2994 R&D Projects: GA ČR(CZ) GA402/05/0115; GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : Markov and semi-Markov processes with rewards * variance of cumulative reward * asymptotic behaviour Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.259, year: 2005

Managing risk and expected financial return from selective expansion of operating room capacity: mean-variance analysis of a hospital's portfolio of surgeons.

Science.gov (United States)

Dexter, Franklin; Ledolter, Johannes

2003-07-01

Surgeons using the same amount of operating room (OR) time differ in their achieved hospital contribution margins (revenue minus variable costs) by >1000%. Thus, to improve the financial return from perioperative facilities, OR strategic decisions should selectively focus additional OR capacity and capital purchasing on a few surgeons or subspecialties. These decisions use estimates of each surgeon's and/or subspecialty's contribution margin per OR hour. The estimates are subject to uncertainty (e.g., from outliers). We account for the uncertainties by using mean-variance portfolio analysis (i.e., quadratic programming). This method characterizes the problem of selectively expanding OR capacity based on the expected financial return and risk of different portfolios of surgeons. The assessment reveals whether the choices, of which surgeons have their OR capacity expanded, are sensitive to the uncertainties in the surgeons' contribution margins per OR hour. Thus, mean-variance analysis reduces the chance of making strategic decisions based on spurious information. We also assess the financial benefit of using mean-variance portfolio analysis when the planned expansion of OR capacity is well diversified over at least several surgeons or subspecialties. Our results show that, in such circumstances, there may be little benefit from further changing the portfolio to reduce its financial risk. Surgeon and subspecialty specific hospital financial data are uncertain, a fact that should be taken into account when making decisions about expanding operating room capacity. We show that mean-variance portfolio analysis can incorporate this uncertainty, thereby guiding operating room management decision-making and reducing the chance of a strategic decision being made based on spurious information.