WorldWideScience

Sample records for genetic variance

  1. Characterizing the evolution of genetic variance using genetic covariance tensors.

    Science.gov (United States)

    Hine, Emma; Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W

    2009-06-12

    Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance-covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations.

  2. Bias-variance decomposition in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Kowaliw Taras

    2016-01-01

    Full Text Available We study properties of Linear Genetic Programming (LGP through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size, the initial population, and the function set used. We confirm and quantify several insights into the practical usage of GP, most notably that (a the variance between runs is primarily due to initialization rather than the selection of training samples, (b parameters can be reasonably optimized to obtain gains in efficacy, and (c functions detrimental to evolvability are easily eliminated, while functions well-suited to the problem can greatly improve performance—therefore, larger and more diverse function sets are always preferable.

  3. The phenome-wide distribution of genetic variance.

    Science.gov (United States)

    Blows, Mark W; Allen, Scott L; Collet, Julie M; Chenoweth, Stephen F; McGuigan, Katrina

    2015-07-01

    A general observation emerging from estimates of additive genetic variance in sets of functionally or developmentally related traits is that much of the genetic variance is restricted to few trait combinations as a consequence of genetic covariance among traits. While this biased distribution of genetic variance among functionally related traits is now well documented, how it translates to the broader phenome and therefore any trait combination under selection in a given environment is unknown. We show that 8,750 gene expression traits measured in adult male Drosophila serrata exhibit widespread genetic covariance among random sets of five traits, implying that pleiotropy is common. Ultimately, to understand the phenome-wide distribution of genetic variance, very large additive genetic variance-covariance matrices (G) are required to be estimated. We draw upon recent advances in matrix theory for completing high-dimensional matrices to estimate the 8,750-trait G and show that large numbers of gene expression traits genetically covary as a consequence of a single genetic factor. Using gene ontology term enrichment analysis, we show that the major axis of genetic variance among expression traits successfully identified genetic covariance among genes involved in multiple modes of transcriptional regulation. Our approach provides a practical empirical framework for the genetic analysis of high-dimensional phenome-wide trait sets and for the investigation of the extent of high-dimensional genetic constraint.

  4. Analysis of Variance Components for Genetic Markers with Unphased Genotypes.

    Science.gov (United States)

    Wang, Tao

    2016-01-01

    An ANOVA type general multi-allele (GMA) model was proposed in Wang (2014) on analysis of variance components for quantitative trait loci or genetic markers with phased or unphased genotypes. In this study, by applying the GMA model, we further examine estimation of the genetic variance components for genetic markers with unphased genotypes based on a random sample from a study population. In one locus and two loci cases, we first derive the least square estimates (LSE) of model parameters in fitting the GMA model. Then we construct estimators of the genetic variance components for one marker locus in a Hardy-Weinberg disequilibrium population and two marker loci in an equilibrium population. Meanwhile, we explore the difference between the classical general linear model (GLM) and GMA based approaches in association analysis of genetic markers with quantitative traits. We show that the GMA model can retain the same partition on the genetic variance components as the traditional Fisher's ANOVA model, while the GLM cannot. We clarify that the standard F-statistics based on the partial reductions in sums of squares from GLM for testing the fixed allelic effects could be inadequate for testing the existence of the variance component when allelic interactions are present. We point out that the GMA model can reduce the confounding between the allelic effects and allelic interactions at least for independent alleles. As a result, the GMA model could be more beneficial than GLM for detecting allelic interactions.

  5. Genetic heterogeneity of residual variance in broiler chickens

    Directory of Open Access Journals (Sweden)

    Hill William G

    2006-11-01

    Full Text Available Abstract Aims were to estimate the extent of genetic heterogeneity in environmental variance. Data comprised 99 535 records of 35-day body weights from broiler chickens reared in a controlled environment. Residual variance within dam families was estimated using ASREML, after fitting fixed effects such as genetic groups and hatches, for each of 377 genetically contemporary sires with a large number of progeny (> 100 males or females each. Residual variance was computed separately for male and female offspring, and after correction for sampling, strong evidence for heterogeneity was found, the standard deviation between sires in within variance amounting to 15–18% of its mean. Reanalysis using log-transformed data gave similar results, and elimination of 2–3% of outlier data reduced the heterogeneity but it was still over 10%. The correlation between estimates for males and females was low, however. The correlation between sire effects on progeny mean and residual variance for body weight was small and negative (-0.1. Using a data set bigger than any yet presented and on a trait measurable in both sexes, this study has shown evidence for heterogeneity in the residual variance, which could not be explained by segregation of major genes unless very few determined the trait.

  6. Genetic variance of tolerance and the toxicant threshold model.

    Science.gov (United States)

    Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

    2012-04-01

    A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change.

  7. Non-genetic variance in pigs: genetic analysis of reproduction and production traits

    NARCIS (Netherlands)

    Sell-Kubiak, E.B.

    2015-01-01

    Abstract Sell-Kubiak, E. (2015). Non-genetic variance in pigs: genetic analysis of reproduction and production traits. PhD thesis, Wageningen University, The Netherlands The main objective of this thesis was to study the origin of random variance in reproduction and production trait

  8. Estimates of genetic variance and variance of predicted genetic merits using pedigree or genomic relationship matrices in six Brown Swiss cattle populations for different traits.

    Science.gov (United States)

    Loberg, A; Dürr, J W; Fikse, W F; Jorjani, H; Crooks, L

    2015-10-01

    The amount of variance captured in genetic estimations may depend on whether a pedigree-based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree-based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population-trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree-based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree-based relationship matrix. The ratio of the genomic to pedigree-based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress. © 2015 Blackwell Verlag GmbH.

  9. 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

  10. Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

    Science.gov (United States)

    Sztepanacz, Jacqueline L.; Blows, Mark W.

    2015-01-01

    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. PMID:25783700

  11. Estimation of genetic variation in residual variance in female and male broiler chickens

    NARCIS (Netherlands)

    Mulder, H.A.; Hill, W.G.; Vereijken, A.; Veerkamp, R.F.

    2009-01-01

    In breeding programs, robustness of animals and uniformity of end product can be improved by exploiting genetic variation in residual variance. Residual variance can be defined as environmental variance after accounting for all identifiable effects. The aims of this study were to estimate genetic va

  12. 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

    There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher

  13. The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance.

    Directory of Open Access Journals (Sweden)

    Simon K G Forsberg

    2015-11-01

    Full Text Available Genome-wide association (GWA analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or "missing heritability". Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1, and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975 as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

  14. Comparison of multiplicative heterogeneous variance adjustment models for genetic evaluations.

    Science.gov (United States)

    Márkus, Sz; Mäntysaari, E A; Strandén, I; Eriksson, J-Å; Lidauer, M H

    2014-06-01

    Two heterogeneous variance adjustment methods and two variance models were compared in a simulation study. The method used for heterogeneous variance adjustment in the Nordic test-day model, which is a multiplicative method based on Meuwissen (J. Dairy Sci., 79, 1996, 310), was compared with a restricted multiplicative method where the fixed effects were not scaled. Both methods were tested with two different variance models, one with a herd-year and the other with a herd-year-month random effect. The simulation study was built on two field data sets from Swedish Red dairy cattle herds. For both data sets, 200 herds with test-day observations over a 12-year period were sampled. For one data set, herds were sampled randomly, while for the other, each herd was required to have at least 10 first-calving cows per year. The simulations supported the applicability of both methods and models, but the multiplicative mixed model was more sensitive in the case of small strata sizes. Estimation of variance components for the variance models resulted in different parameter estimates, depending on the applied heterogeneous variance adjustment method and variance model combination. Our analyses showed that the assumption of a first-order autoregressive correlation structure between random-effect levels is reasonable when within-herd heterogeneity is modelled by year classes, but less appropriate for within-herd heterogeneity by month classes. Of the studied alternatives, the multiplicative method and a variance model with a random herd-year effect were found most suitable for the Nordic test-day model for dairy cattle evaluation.

  15. 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 fo

  16. Genetically controlled environmental variance for sternopleural bristles in Drosophila melanogaster - an experimental test of a heterogeneous variance model

    DEFF Research Database (Denmark)

    Sørensen, Anders Christian; Kristensen, Torsten Nygård; Loeschcke, Volker

    2007-01-01

    quantitative genetics model based on the infinitesimal model, and an extension of this model. In the extended model it is assumed that each individual has its own environmental variance and that this heterogeneity of variance has a genetic component. The heterogeneous variance model was favoured by the data......, indicating that the environmental variance is partly under genetic control. If this heterogeneous variance model also applies to livestock, it would be possible to select for animals with a higher uniformity of products across environmental regimes. Also for evolutionary biology the results are of interest...

  17. 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

    , 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 ... to the most parsimonious variance component model, genetic factors accounted for 57% (CI: 42-72%, P variance in ECP levels, whereas the remainder (43%) was ascribable to non-shared environmental factors. The genetic correlation between ECP and airway responsiveness to methacholine...... 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....

  18. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis

    Science.gov (United States)

    Huang, Wen; Mackay, Trudy F. C.

    2016-01-01

    Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits. PMID:27812106

  19. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis.

    Directory of Open Access Journals (Sweden)

    Wen Huang

    2016-11-01

    Full Text Available Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs. Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA, providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.

  20. Sex Modifies Genetic Effects on Residual Variance in Urinary Calcium Excretion in Rat (Rattus norvegicus)

    OpenAIRE

    Perry, Guy M. L.; Nehrke, Keith W.; Bushinsky, David A; Reid, Robert; Lewandowski, Krista L.; Hueber, Paul; Scheinman, Steven J.

    2012-01-01

    Conventional genetics assumes common variance among alleles or genetic groups. However, evidence from vertebrate and invertebrate models suggests that residual genotypic variance may itself be under partial genetic control. Such a phenomenon would have great significance: high-variability alleles might confound the detection of “classically” acting genes or scatter predicted evolutionary outcomes among unpredicted trajectories. Of the few works on this phenomenon, many implicate sex in some a...

  1. Rapid Divergence of Genetic Variance-Covariance Matrix within a Natural Population

    NARCIS (Netherlands)

    Doroszuk, A.; Wojewodzic, M.W.; Gort, G.; Kammenga, J.E.

    2008-01-01

    The matrix of genetic variances and covariances (G matrix) represents the genetic architecture of multiple traits sharing developmental and genetic processes and is central for predicting phenotypic evolution. These predictions require that the G matrix be stable. Yet the timescale and conditions pr

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

    NARCIS (Netherlands)

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

    2013-01-01

    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 homogene

  3. 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

  4. Genetic variance of sunflower yield components - Heliantus annuus L.

    OpenAIRE

    Hladni Nada; Škorić Dragan; Kraljević-Balalić Marija

    2003-01-01

    The main goals of sunflower breeding in Yugoslavia and abroad are increased seed yield and oil content per unit area and increased resistance to diseases, insects and stress conditions via an optimization of plant architecture. In order to determine the mode of inheritance, gene effects and correlations of total leaf number per plant, total leaf area and plant height, six genetically divergent inbred lines of sunflower were subjected to half diallel crosses. Significant differences in mean va...

  5. Genetic factors explain half of all variance in serum eosinophil cationic protein.

    Science.gov (United States)

    Elmose, C; Sverrild, A; van der Sluis, S; Kyvik, K O; Backer, V; Thomsen, S F

    2014-12-01

    Eosinophil cationic protein (ECP) is one of four basic proteins of the secretory granules of eosinophils. It has a variety of functions associated with inflammatory responses. Little is known about the causes for variation in serum ECP levels. To identify factors associated 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. 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. Sex (regression coefficient = -0.107, P variance component model, genetic factors accounted for 57% (CI: 42-72%, P variance in ECP levels, whereas the remainder (43%) was ascribable to non-shared environmental factors. The genetic correlation between ECP and airway responsiveness to methacholine was statistically non-significant (r = -0.11, P = 0.50). 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. © 2014 John Wiley & Sons Ltd.

  6. 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...

  7. Genetic variance in the adiponutrin gene family and childhood obesity.

    Directory of Open Access Journals (Sweden)

    Lovisa E Johansson

    Full Text Available AIM: The adiponutrin gene family consists of five genes (PNPLA1-5 coding for proteins with both lipolytic and lipogenic properties. PNPLA3 has previously been associated with adult obesity. Here we investigated the possible association between genetic variants in these genes and childhood and adolescent obesity. METHODS/RESULTS: Polymorphisms in the five genes of the adiponutrin gene family were selected and genotyped using the Sequenom platform in a childhood and adolescent obesity case-control study. Six variants in PNPLA1 showed association with obesity (rs9380559, rs12212459, rs1467912, rs4713951, rs10947600, and rs12199580, p0.05. When analyzing these SNPs in relation to phenotypes, two SNPs in the PNPLA3 gene showed association with insulin sensitivity (rs12483959: beta = -0.053, p = 0.016, and rs2072907: beta = -0.049, p = 0.024. No associations were seen for PNPLA2, PNPLA4, and PNPLA5. CONCLUSIONS: Genetic variation in the adiponutrin gene family does not seem to contribute strongly to obesity in children and adolescents. PNPLA1 exhibited a modest effect on obesity and PNPLA3 on insulin sensitivity. These data, however, require confirmation in other cohorts and ethnic groups.

  8. The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

    Science.gov (United States)

    Miller, Geoffrey F.; Penke, Lars

    2007-01-01

    Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

  9. Genetic variances, trends and mode of inheritance for hip and elbow dysplasia in Finnish dog populations

    NARCIS (Netherlands)

    Mäki, K.; Groen, A.F.; Liinamo, A.E.; Ojala, M.

    2002-01-01

    The aims of this study were to assess genetic variances, trends and mode of inheritance for hip and elbow dysplasia in Finnish dog populations. The influence of time-dependent fixed effects in the model when estimating the genetic trends was also studied. Official hip and elbow dysplasia screening

  10. Selection for uniformity in livestock by exploiting genetic heterogeneity of environmental variance

    NARCIS (Netherlands)

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

    2008-01-01

    In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, b

  11. The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

    Science.gov (United States)

    Miller, Geoffrey F.; Penke, Lars

    2007-01-01

    Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

  12. Population Bottlenecks Increase Additive Genetic Variance But Do Not Break a Selection Limit in Rainforest Drosophila

    DEFF Research Database (Denmark)

    van Heerwaarden, Belinda; Willi, Yvonne; Kristensen, Torsten N

    2008-01-01

    actually increase additive genetic variance. This has been an important issue in conservation genetics where it has been suggested that small population size might actually experience an increase rather than a decrease in the rate of adaptation. Here we test if bottlenecks can break a selection limit...... for desiccation resistance in the rain forest-restricted fly Drosophila bunnanda. After one generation of single-pair mating, additive genetic variance for desiccation resistance increased to a significant level, on average higher than for the control lines. Line crosses revealed that both dominance and epistatic...... effects were responsible for the divergence in desiccation resistance between the original control and a bottlenecked line exhibiting increased additive genetic variance for desiccation resistance. However, when bottlenecked lines were selected for increased desiccation resistance, there was only a small...

  13. Genetic variance of sunflower yield components - Heliantus annuus L.

    Directory of Open Access Journals (Sweden)

    Hladni Nada

    2003-01-01

    Full Text Available The main goals of sunflower breeding in Yugoslavia and abroad are increased seed yield and oil content per unit area and increased resistance to diseases, insects and stress conditions via an optimization of plant architecture. In order to determine the mode of inheritance, gene effects and correlations of total leaf number per plant, total leaf area and plant height, six genetically divergent inbred lines of sunflower were subjected to half diallel crosses. Significant differences in mean values of all the traits were found in the F1 and F2 generations. Additive gene effects were more important in the inheritance of total leaf number per plant and plant height, while in the case of total leaf area per plant the nonadditive ones were more important looking at all the combinations in the F1 and F2 generations. The average degree of dominance (Hi/D1/2 was lower than one for total leaf number per plant and plant height, so the mode of inheritance was partial dominance, while with total leaf area the value was higher than one, indicating super dominance as the mode of inheritance. Significant positive correlation was found: between total leaf area per plant and total leaf number per plant (0.285* and plant height (0.278*. The results of the study are of importance for further sunflower breeding work.

  14. Increasing genetic variance of body mass index during the Swedish obesity epidemic

    DEFF Research Database (Denmark)

    Rokholm, Benjamin; Silventoinen, Karri; Tynelius, Per

    2011-01-01

    There is no doubt that the dramatic worldwide increase in obesity prevalence is due to changes in environmental factors. However, twin and family studies suggest that genetic differences are responsible for the major part of the variation in adiposity within populations. Recent studies show...... that the genetic effects on body mass index (BMI) may be stronger when combined with presumed risk factors for obesity. We tested the hypothesis that the genetic variance of BMI has increased during the obesity epidemic....

  15. Genetic basis of between-individual and within-individual variance of docility.

    Science.gov (United States)

    Martin, J G A; Pirotta, E; Petelle, M B; Blumstein, D T

    2017-04-01

    Between-individual variation in phenotypes within a population is the basis of evolution. However, evolutionary and behavioural ecologists have mainly focused on estimating between-individual variance in mean trait and neglected variation in within-individual variance, or predictability of a trait. In fact, an important assumption of mixed-effects models used to estimate between-individual variance in mean traits is that within-individual residual variance (predictability) is identical across individuals. Individual heterogeneity in the predictability of behaviours is a potentially important effect but rarely estimated and accounted for. We used 11 389 measures of docility behaviour from 1576 yellow-bellied marmots (Marmota flaviventris) to estimate between-individual variation in both mean docility and its predictability. We then implemented a double hierarchical animal model to decompose the variances of both mean trait and predictability into their environmental and genetic components. We found that individuals differed both in their docility and in their predictability of docility with a negative phenotypic covariance. We also found significant genetic variance for both mean docility and its predictability but no genetic covariance between the two. This analysis is one of the first to estimate the genetic basis of both mean trait and within-individual variance in a wild population. Our results indicate that equal within-individual variance should not be assumed. We demonstrate the evolutionary importance of the variation in the predictability of docility and illustrate potential bias in models ignoring variation in predictability. We conclude that the variability in the predictability of a trait should not be ignored, and present a coherent approach for its quantification. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  16. Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.

    Science.gov (United States)

    He, Liang; Sillanpää, Mikko J; Silventoinen, Karri; Kaprio, Jaakko; Pitkäniemi, Janne

    2016-04-01

    Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene-environment (G×E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametricG×Einteraction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more

  17. Estimation of the proportion of genetic variance explained by molecular markers

    OpenAIRE

    Bearzoti,Eduardo; Vencovsky, Roland

    1998-01-01

    Estimation of the proportion of genetic variance explained by molecular markers (p) plays an important role in basic studies of quantitative traits, as well as in marker-assisted selection (MAS), if the selection index proposed by Lande and Thompson (Genetics 124: 743-756, 1990) is used. Frequently, the coefficient of determination (R2) is used to account for this proportion. In the present study, a simple estimator of p is presented, which is applicable when a multiple regression approach is...

  18. Genetic control of residual variance of yearling weight in nellore beef cattle

    NARCIS (Netherlands)

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

    2017-01-01

    There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them

  19. GSEVM v.2: MCMC software to analyse genetically structured environmental variance models

    DEFF Research Database (Denmark)

    Ibáñez-Escriche, N; Garcia, M; Sorensen, D

    2010-01-01

    This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix executable programs, the user's guide, and some example files are freely availab...

  20. Shared genetic variance between obesity and white matter integrity in Mexican Americans

    Science.gov (United States)

    Spieker, Elena A.; Kochunov, Peter; Rowland, Laura M.; Sprooten, Emma; Winkler, Anderson M.; Olvera, Rene L.; Almasy, Laura; Duggirala, Ravi; Fox, Peter T.; Blangero, John; Glahn, David C.; Curran, Joanne E.

    2015-01-01

    Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m2) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h2 = 0.58), WC (h2 = 0.57), and FA (h2 = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors. PMID:25763009

  1. Shared genetic variance between obesity and white matter integrity in Mexican-americans

    Directory of Open Access Journals (Sweden)

    Elena A Spieker

    2015-02-01

    Full Text Available Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N=761, 58% females, ages 18-81y; 41.3±14.5 from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity ((body mass index (BMI; kg/m2 and waist circumference (WC; in and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy. Whole-brain average and regional fractional anisotropy values for ten major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7×1.7×3 mm; 55 directions. Additive genetic factors explained intersubject variance in BMI (heritability, h2=0.58, WC (h2=0.57, and FA (h2=0.49. FA shared significant portions of genetic variance with BMI in the genu (ρG = -0.25, body (ρG = -0.30, and splenium (ρG = -0.26 of the corpus callosum, internal capsule (ρG = -0.29, and thalamic radiation (ρG = -0.31 (all p’s = .043. The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = -0.39, p = .020; ρG = -0.39, p = .030, which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors.

  2. Fertilization success and the estimation of genetic variance in sperm competitiveness.

    Science.gov (United States)

    Garcia-Gonzalez, Francisco; Evans, Jonathan P

    2011-03-01

    A key question in sexual selection is whether the ability of males to fertilize eggs under sperm competition exhibits heritable genetic variation. Addressing this question poses a significant problem, however, because a male's ability to win fertilizations ultimately depends on the competitive ability of rival males. Attempts to partition genetic variance in sperm competitiveness, as estimated from measures of fertilization success, must therefore account for stochastic effects due to the random sampling of rival sperm competitors. In this contribution, we suggest a practical solution to this problem. We advocate the use of simple cross-classified breeding designs for partitioning sources of genetic variance in sperm competitiveness and fertilization success and show how these designs can be used to avoid stochastic effects due to the random sampling of rival sperm competitors. We illustrate the utility of these approaches by simulating various scenarios for estimating genetic parameters in sperm competitiveness, and show that the probability of detecting additive genetic variance in this trait is restored when stochastic effects due to the random sampling of rival sperm competitors are controlled. Our findings have important implications for the study of the evolutionary maintenance of polyandry.

  3. 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

    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....... 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...

  4. Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.

    Science.gov (United States)

    Schmitt, J Eric; Lenroot, Rhoshel K; Ordaz, Sarah E; Wallace, Gregory L; Lerch, Jason P; Evans, Alan C; Prom, Elizabeth C; Kendler, Kenneth S; Neale, Michael C; Giedd, Jay N

    2009-08-01

    The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.

  5. Genetically Determined Variation in Lysis Time Variance in the Bacteriophage φX174.

    Science.gov (United States)

    Baker, Christopher W; Miller, Craig R; Thaweethai, Tanayott; Yuan, Jeffrey; Baker, Meghan Hollibaugh; Joyce, Paul; Weinreich, Daniel M

    2016-04-07

    Researchers in evolutionary genetics recently have recognized an exciting opportunity in decomposing beneficial mutations into their proximal, mechanistic determinants. The application of methods and concepts from molecular biology and life history theory to studies of lytic bacteriophages (phages) has allowed them to understand how natural selection sees mutations influencing life history. This work motivated the research presented here, in which we explored whether, under consistent experimental conditions, small differences in the genome of bacteriophage φX174 could lead to altered life history phenotypes among a panel of eight genetically distinct clones. We assessed the clones' phenotypes by applying a novel statistical framework to the results of a serially sampled parallel infection assay, in which we simultaneously inoculated each of a large number of replicate host volumes with ∼1 phage particle. We sequentially plated the volumes over the course of infection and counted the plaques that formed after incubation. These counts served as a proxy for the number of phage particles in a single volume as a function of time. From repeated assays, we inferred significant, genetically determined heterogeneity in lysis time and burst size, including lysis time variance. These findings are interesting in light of the genetic and phenotypic constraints on the single-protein lysis mechanism of φX174. We speculate briefly on the mechanisms underlying our results, and we discuss the potential importance of lysis time variance in viral evolution.

  6. Genetically Determined Variation in Lysis Time Variance in the Bacteriophage φX174

    Directory of Open Access Journals (Sweden)

    Christopher W. Baker

    2016-04-01

    Full Text Available Researchers in evolutionary genetics recently have recognized an exciting opportunity in decomposing beneficial mutations into their proximal, mechanistic determinants. The application of methods and concepts from molecular biology and life history theory to studies of lytic bacteriophages (phages has allowed them to understand how natural selection sees mutations influencing life history. This work motivated the research presented here, in which we explored whether, under consistent experimental conditions, small differences in the genome of bacteriophage φX174 could lead to altered life history phenotypes among a panel of eight genetically distinct clones. We assessed the clones’ phenotypes by applying a novel statistical framework to the results of a serially sampled parallel infection assay, in which we simultaneously inoculated each of a large number of replicate host volumes with ∼1 phage particle. We sequentially plated the volumes over the course of infection and counted the plaques that formed after incubation. These counts served as a proxy for the number of phage particles in a single volume as a function of time. From repeated assays, we inferred significant, genetically determined heterogeneity in lysis time and burst size, including lysis time variance. These findings are interesting in light of the genetic and phenotypic constraints on the single-protein lysis mechanism of φX174. We speculate briefly on the mechanisms underlying our results, and we discuss the potential importance of lysis time variance in viral evolution.

  7. A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference

    Directory of Open Access Journals (Sweden)

    Heringstad Bjørg

    2010-07-01

    Full Text Available Abstract Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (covariance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative" or "non-informative" with respect to genetic (covariance components. The "non-informative" individuals are characterized by their Mendelian sampling deviations (deviance from the mid-parent mean being completely confounded with a single residual on the underlying liability scale. For threshold models, residual variance on the underlying scale is not identifiable. Hence, variance of fully confounded Mendelian sampling deviations cannot be identified either, but can be inferred from the between-family variation. In the new algorithm, breeding values are sampled as in a standard animal model using the full relationship matrix, but genetic (covariance components are inferred from the sampled breeding values and relationships between "informative" individuals (usually parents only. The latter is analogous to a sire-dam model (in cases with no individual records on the parents. Results When applied to simulated data sets, the standard animal threshold model failed to produce useful results since samples of genetic variance always drifted towards infinity, while the new algorithm produced proper parameter estimates essentially identical to the results from a sire-dam model (given the fact that no individual records exist for the parents. Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to

  8. 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.

  9. Estimation of (co)variance components and genetic parameters of greasy fleece weights in Muzaffarnagari sheep.

    Science.gov (United States)

    Mandal, A; Neser, F W C; Roy, R; Rout, P K; Notter, D R

    2009-02-01

    Variance components and genetic parameters for greasy fleece weights of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 29 years (1976 to 2004) were estimated by restricted maximum likelihood (REML), fitting six animal models including various combinations of maternal effects. Data on body weights at 6 (W6) and 12 months (W12) of age were also included in the study. Records of 2807 lambs descended from 160 rams and 1202 ewes were used for the study. Direct heritability estimates for fleece weight at 6 (FW6) and 12 months of age (FW12), and total fleece weights up to 1 year of age (TFW) were 0.14, 0.16 and 0.25, respectively. Maternal genetic and permanent environmental effects did not significantly influence any of the traits under study. Genetic correlations among fleece weights and body weights were obtained from multivariate analyses. Direct genetic correlations of FW6 with W6 and W12 were relatively large, ranging from 0.61 to 0.67, but only moderate genetic correlations existed between FW12 and W6 (0.39) and between FW12 and W12 (0.49). The genetic correlation between FW6 and FW12 was very high (0.95), but the corresponding phenotypic correlation was much lower (0.28). Heritability estimates for all traits were at least 0.15, indicating that there is potential for their improvement by selection. The moderate to high positive genetic correlations between fleece weights and body weights at 6 and 12 months of age suggest that some of the genetic factors that influence animal growth also influence wool growth. Thus selection to improve the body weights or fleece weights at 6 months of age will also result in genetic improvement of fleece weights at subsequent stages of growth.

  10. Effect of captivity on genetic variance for five traits in the large milkweed bug (Oncopeltus fasciatus).

    Science.gov (United States)

    Rodríguez-Clark, K M

    2004-07-01

    Understanding the changes in genetic variance which may occur as populations move from nature into captivity has been considered important when populations in captivity are used as models of wild ones. However, the inherent significance of these changes has not previously been appreciated in a conservation context: are the methods aimed at founding captive populations with gene diversity representative of natural populations likely also to capture representative quantitative genetic variation? Here, I investigate changes in heritability and a less traditional measure, evolvability, between nature and captivity for the large milkweed bug, Oncopeltus fasciatus, to address this question. Founders were collected from a 100-km transect across the north-eastern US, and five traits (wing colour, pronotum colour, wing length, early fecundity and later fecundity) were recorded for founders and for their offspring during two generations in captivity. Analyses reveal significant heritable variation for some life history and morphological traits in both environments, with comparable absolute levels of evolvability across all traits (0-30%). Randomization tests show that while changes in heritability and total phenotypic variance were highly variable, additive genetic variance and evolvability remained stable across the environmental transition in the three morphological traits (changing 1-2% or less), while they declined significantly in the two life-history traits (5-8%). Although it is unclear whether the declines were due to selection or gene-by-environment interactions (or both), such declines do not appear inevitable: captive populations with small numbers of founders may contain substantial amounts of the evolvability found in nature, at least for some traits.

  11. Very low levels of direct additive genetic variance in fitness and fitness components in a red squirrel population.

    Science.gov (United States)

    McFarlane, S Eryn; Gorrell, Jamieson C; Coltman, David W; Humphries, Murray M; Boutin, Stan; McAdam, Andrew G

    2014-05-01

    A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation-selection balance. Here, we used a long-term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade-offs between fitness components, such as male and female fitness or fitness in high- and low-resource environments. "Animal model" analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population.

  12. The effect of a population bottleneck on the evolution of genetic variance/covariance structure.

    Science.gov (United States)

    Jarvis, J P; Cropp, S N; Vaughn, T T; Pletscher, L S; King-Ellison, K; Adams-Hunt, E; Erickson, C; Cheverud, J M

    2011-10-01

    It is well known that standard population genetic theory predicts decreased additive genetic variance (V(a) ) following a population bottleneck and that theoretical models including interallelic and intergenic interactions indicate such loss may be avoided. However, few empirical data from multicellular model systems are available, especially regarding variance/covariance (V/CV) relationships. Here, we compare the V/CV structure of seventeen traits related to body size and composition between control (60 mating pairs/generation) and bottlenecked (2 mating pairs/generation; average F = 0.39) strains of mice. Although results for individual traits vary considerably, multivariate analysis indicates that V(a) in the bottlenecked populations is greater than expected. Traits with patterns and amounts of epistasis predictive of enhanced V(a) also show the largest deviations from additive expectations. Finally, the correlation structure of weekly weights is not significantly different between control and experimental lines but correlations between necropsy traits do differ, especially those involving the heart, kidney and tail length. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

  13. Estimation of the proportion of genetic variance explained by molecular markers

    Directory of Open Access Journals (Sweden)

    Bearzoti Eduardo

    1998-01-01

    Full Text Available Estimation of the proportion of genetic variance explained by molecular markers (p plays an important role in basic studies of quantitative traits, as well as in marker-assisted selection (MAS, if the selection index proposed by Lande and Thompson (Genetics 124: 743-756, 1990 is used. Frequently, the coefficient of determination (R2 is used to account for this proportion. In the present study, a simple estimator of p is presented, which is applicable when a multiple regression approach is used, and progenies are evaluated in replicated trials. The associated sampling distribution was obtained and compared with that of R2. Simulations indicated that, when the number of evaluated progenies is small, the statistics are not satisfactory, in general, due to bias and/or low precision. Coefficient R2 was found adequate in situations where p is high. If a large number of progenies is evaluated (say, a few hundreds, then the proposed estimator appears to be better, with acceptable precision and considerably lower bias than R2. A normal approximation to the sampling distribution of is given, using Taylor's expansion of the expectation and variance of this statistic. Approximate confidence intervals for p, based on normal distribution, are reasonable, if the number of progenies is large. The use of in MAS is illustrated for estimation of the weight given to the molecular score, when a selection index is used.

  14. Intra-population genetic variance for grain iron and zinc contents and agronomic traits in pearl millet

    Institute of Scientific and Technical Information of China (English)

    Mahalingam Govindaraj; Kedar N.Rai; Ponnusamy Shanmugasundaram

    2016-01-01

    Crop biofortification is a sustainable approach for fighting micronutrient malnutrition in the world. The estimation of variance components in genetically broad-based populations provides information about their genetic architecture, allowing the design of an appropriate biofortification breeding method for cross-pollinated crops such as pearl millet. The objective of this study was to estimate intra-population genetic variance using self(S1) and half-sib(HS) progenies in two populations, AIMP92901 and ICMR312. Field trials were evaluated in two contrasting seasons(2009 rainy and 2010 summer; otherwise called environments) in Alfisols at ICRISAT, Patancheru. Analyses of variance showed highly significant variation for S1 s and HS progenies, reflecting high within-population genetic variation for both micronutrients and other key traits. However, the HS showed narrow ranges and lower genetic variances than the S1 for all of the traits. The micronutrients were highly positively correlated in S1(r = 0.77 to 0.86; P < 0.01) and HS(r = 0.74 to 0.77; P < 0.01)progenies of both populations, implying concurrent genetic improvement for both micronutrients. The genetic variance component was different among populations for Fe and Zn contents across environments, with AIMP92901 showing a greater proportion of dominance and ICMR312 greater additive variance for these micronutrients. The estimates of variance(additive and dominance) were specific for each population, given their dependence on the additive and dominance effects of the segregating loci, which also differ among populations. The possible causes for such differences were discussed. The results showed that the expression of these micronutrients in pearl millet shows largely additive variance, so that breeding high-iron hybrids will require incorporation of these micronutrient traits into both parental lines.

  15. Intra-population genetic variance for grain iron and zinc contents and agronomic traits in pearl millet

    Institute of Scientific and Technical Information of China (English)

    Mahalingam Govindaraj; Kedar N. Rai; Ponnusamy Shanmugasundaram

    2016-01-01

    Crop biofortification is a sustainable approach for fighting micronutrient malnutrition in the world. The estimation of variance components in genetically broad-based populations provides information about their genetic architecture, allowing the design of an appropriate biofortification breeding method for cross-pollinated crops such as pearl millet. The objective of this study was to estimate intra-population genetic variance using self (S1) and half-sib (HS) progenies in two populations, AIMP92901 and ICMR312. Field trials were evaluated in two contrasting seasons (2009 rainy and 2010 summer; otherwise called environments) in Alfisols at ICRISAT, Patancheru. Analyses of variance showed highly significant variation for S1s and HS progenies, reflecting high within-population genetic variation for both micronutrients and other key traits. However, the HS showed narrow ranges and lower genetic variances than the S1 for all of the traits. The micronutrients were highly positively correlated in S1 (r=0.77 to 0.86;P<0.01) and HS (r=0.74 to 0.77;P<0.01) progenies of both populations, implying concurrent genetic improvement for both micronutrients. The genetic variance component was different among populations for Fe and Zn contents across environments, with AIMP92901 showing a greater proportion of dominance and ICMR312 greater additive variance for these micronutrients. The estimates of variance (additive and dominance) were specific for each population, given their dependence on the additive and dominance effects of the segregating loci, which also differ among populations. The possible causes for such differences were discussed. The results showed that the expression of these micronutrients in pearl millet shows largely additive variance, so that breeding high-iron hybrids will require incorporation of these micronu-trient traits into both parental lines.

  16. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  17. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M.You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design(MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters.Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline(http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  18. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Directory of Open Access Journals (Sweden)

    Frank M. You

    2016-04-01

    Full Text Available The type 2 modified augmented design (MAD2 is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html.

  19. 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.

  20. The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population.

    Science.gov (United States)

    Matsuda, H; Iwaisaki, H

    2002-01-01

    In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.

  1. Estimates of (co)variance components and genetic parameters for growth traits of Avikalin sheep.

    Science.gov (United States)

    Prince, Leslie Leo L; Gowane, Gopal R; Chopra, Ashish; Arora, Amrit L

    2010-08-01

    (Co)variance components and genetic parameters for various growth traits of Avikalin sheep maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by Restricted Maximum Likelihood, fitting six animal models with various combinations of direct and maternal effects. Records of 3,840 animals descended from 257 sires and 1,194 dams were taken for this study over a period of 32 years (1977-2008). Direct heritability estimates (from best model as per likelihood ratio test) for weight at birth, weaning, 6 and 12 months of age, and average daily gain from birth to weaning, weaning to 6 months, and 6 to 12 months were 0.28 +/- 0.03, 0.20 +/- 0.03, 0.28 +/- 0.07, 0.15 +/- 0.04, 0.21 +/- 0.03, 0.16 and 0.03 +/- 0.03, respectively. Maternal heritability for traits declined as animal grows older and it was not at all evident at adult age and for post-weaning daily gain. Maternal permanent environmental effect (c(2)) declined significantly with advancement of age of animal. A small effect of c(2) on post-weaning weights was probably a carryover effect of pre-weaning maternal influence. A significant large negative genetic correlation was observed between direct and maternal genetic effects for all the traits, indicating antagonistic pleiotropy, which needs special care while formulating breeding plans. A fair rate of genetic progress seems possible in the flock by selection for all traits, but direct and maternal genetic correlation needs to be taken in to consideration.

  2. Population divergence along lines of genetic variance and covariance in the invasive plant Lythrum salicaria in eastern North America.

    Science.gov (United States)

    Colautti, Robert I; Barrett, Spencer C H

    2011-09-01

    Evolution during biological invasion may occur over contemporary timescales, but the rate of evolutionary change may be inhibited by a lack of standing genetic variation for ecologically relevant traits and by fitness trade-offs among them. The extent to which these genetic constraints limit the evolution of local adaptation during biological invasion has rarely been examined. To investigate genetic constraints on life-history traits, we measured standing genetic variance and covariance in 20 populations of the invasive plant purple loosestrife (Lythrum salicaria) sampled along a latitudinal climatic gradient in eastern North America and grown under uniform conditions in a glasshouse. Genetic variances within and among populations were significant for all traits; however, strong intercorrelations among measurements of seedling growth rate, time to reproductive maturity and adult size suggested that fitness trade-offs have constrained population divergence. Evidence to support this hypothesis was obtained from the genetic variance-covariance matrix (G) and the matrix of (co)variance among population means (D), which were 79.8% (95% C.I. 77.7-82.9%) similar. These results suggest that population divergence during invasive spread of L. salicaria in eastern North America has been constrained by strong genetic correlations among life-history traits, despite large amounts of standing genetic variation for individual traits. © 2011 The Author(s).

  3. Using SNP markers to estimate additive, dominance and imprinting genetic variance

    DEFF Research Database (Denmark)

    Lopes, M S; Bastiaansen, J W M; Janss, Luc

    The contributions of additive, dominance and imprinting effects to the variance of number of teats (NT) were evaluated in two purebred pig populations using SNP markers. Three different random regression models were evaluated, accounting for the mean and: 1) additive effects (MA), 2) additive...... and dominance effects (MAD) and 3) additive, dominance and imprinting effects (MADI). Additive heritability estimates were 0.30, 0.28 and 0.27-0.28 in both lines using MA, MAD and MADI, respectively. Dominance heritability ranged from 0.06 to 0.08 using MAD and MADI. Imprinting heritability ranged from 0.......01 to 0.02. Dominance effects make an important contribution to the genetic variation of NT in the two lines evaluated. Imprinting effects appeared less important for NT than additive and dominance effects. The SNP random regression model presented and evaluated in this study is a feasible approach...

  4. The ARMC5 gene shows extensive genetic variance in primary macronodular adrenocortical hyperplasia

    Science.gov (United States)

    Correa, Ricardo; Zilbermint, Mihail; Berthon, Annabel; Espiard, Stephanie; Batsis, Maria; Papadakis, Georgios Z.; Xekouki, Paraskevi; Lodish, Maya B.; Bertherat, Jerome; Faucz, Fabio R.; Stratakis, Constantine A.

    2015-01-01

    Objective Primary macronodular adrenal hyperplasia (PMAH) is a rare type of Cushing’s syndrome (CS) that results in increased cortisol production and bilateral enlargement of the adrenal glands. Recent work showed that the disease may be caused by germline and somatic mutations in the ARMC5 gene, a likely tumor-suppressor gene (TSG). We investigated 20 different adrenal nodules from one patient with PMAH for ARMC5 somatic sequence changes. Design All of the nodules where obtained from a single patient who underwent bilateral adrenalectomy. DNA was extracted by standard protocols and the ARMC5 sequence was determined by the Sanger method. Results Sixteen of 20 adrenocortical nodules harbored, in addition to what appeared to be the germline mutation, a second somatic variant. The p.Trp476* sequence change was present in all 20 nodules, as well as in normal tissue from the adrenal capsule, identifying it as the germline defect; each of the 16 other variants were found in different nodules: 6 were frame shift, 4 were missense, 3 were nonsense, and 1 was a splice site variation. Allelic losses were confirmed in 2 of the nodules. Conclusion This is the most genetic variance of the ARMC5 gene ever described in a single patient with PMAH: each of 16 adrenocortical nodules had a second new, “private”, and -in most cases- completely inactivating ARMC5 defect, in addition to the germline mutation. The data support the notion that ARMC5 is a TSG that needs a second, somatic hit, to mediate tumorigenesis leading to polyclonal nodularity; however, the driver of this extensive genetic variance of the second ARMC5 allele in adrenocortical tissue in the context of a germline defect and PMAH remains a mystery. PMID:26162405

  5. fullfact: an R package for the analysis of genetic and maternal variance components from full factorial mating designs.

    Science.gov (United States)

    Houde, Aimee Lee S; Pitcher, Trevor E

    2016-03-01

    Full factorial breeding designs are useful for quantifying the amount of additive genetic, nonadditive genetic, and maternal variance that explain phenotypic traits. Such variance estimates are important for examining evolutionary potential. Traditionally, full factorial mating designs have been analyzed using a two-way analysis of variance, which may produce negative variance values and is not suited for unbalanced designs. Mixed-effects models do not produce negative variance values and are suited for unbalanced designs. However, extracting the variance components, calculating significance values, and estimating confidence intervals and/or power values for the components are not straightforward using traditional analytic methods. We introduce fullfact - an R package that addresses these issues and facilitates the analysis of full factorial mating designs with mixed-effects models. Here, we summarize the functions of the fullfact package. The observed data functions extract the variance explained by random and fixed effects and provide their significance. We then calculate the additive genetic, nonadditive genetic, and maternal variance components explaining the phenotype. In particular, we integrate nonnormal error structures for estimating these components for nonnormal data types. The resampled data functions are used to produce bootstrap-t confidence intervals, which can then be plotted using a simple function. We explore the fullfact package through a worked example. This package will facilitate the analyses of full factorial mating designs in R, especially for the analysis of binary, proportion, and/or count data types and for the ability to incorporate additional random and fixed effects and power analyses.

  6. Genetic and phenotypic variance and covariance components for methane emission and postweaning traits in Angus cattle.

    Science.gov (United States)

    Donoghue, K A; Bird-Gardiner, T; Arthur, P F; Herd, R M; Hegarty, R F

    2016-04-01

    Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that

  7. The effect of genetic drift on the variance/covariance components generated by multilocus additive x additive epistatic systems.

    Science.gov (United States)

    López-Fanjul, Carlos; Fernández, Almudena; Toro, Miguel A

    2006-03-21

    The effect of population bottlenecks on the components of the genetic variance/covariance generated by n neutral independent additive x additive loci has been studied theoretically. In its simplest version, this situation can be modelled by specifying the allele frequencies and homozygous effects at each locus, and an additional factor measuring the strength of the n-th order epistatic interaction. The variance/covariance components in an infinitely large panmictic population (ancestral components) were compared with their expected values at equilibrium over replicates randomly derived from the base population, after t bottlenecks of size N (derived components). Formulae were obtained giving the derived components (and the between-line variance) as functions of the ancestral ones (alternatively, in terms of allele frequencies and effects) and the corresponding inbreeding coefficient F(t). The n-th order derived component of the genetic variance/covariance is continuously eroded by inbreeding, but the remaining components may increase initially until a critical F(t) value is attained, which is inversely related to the order of the pertinent component, and subsequently decline to zero. These changes can be assigned to the between-line variances/covariances of gene substitution and epistatic effects induced by drift. Numerical examples indicate that: (1) the derived additive variance/covariance component will generally exceed its ancestral value unless epistasis is weak; (2) the derived epistatic variance/covariance components will generally exceed their ancestral values unless allele frequencies are extreme; (3) for systems showing equal ancestral additive and total non-additive variance/covariance components, those including a smaller number of epistatic loci may generate a larger excess in additive variance/covariance after bottlenecks than others involving a larger number of loci, provided that F(t) is low. Our results indicate that it is unlikely that the rate of

  8. Genetic and Environmental Variance Among F2 Families in a Commercial Breeding Program for Perennial Ryegrass (Lolium perenne L.)

    DEFF Research Database (Denmark)

    Fé, Dario; Greve-Pedersen, Morten; Jensen, Christian Sig

    2013-01-01

    In the joint project “FORAGESELECT”, we aim to implement Genome Wide Selection (GWS) in breeding of perennial ryegrass (Lolium perenne L.), in order to increase genetic response in important agronomic traits such as yield, seed production, stress tolerance and disease resistance, while decreasing...... of this study was to estimate the genetic and environmental variance in the training set composed of F2 families selected from a ten year breeding period. Variance components were estimated on 1193 of those families, sown in 2001, 2003 and 2005 in five locations around Europe. Families were tested together...

  9. Knowledge extraction algorithm for variances handling of CP using integrated hybrid genetic double multi-group cooperative PSO and DPSO.

    Science.gov (United States)

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2012-04-01

    Although the clinical pathway (CP) predefines predictable standardized care process for a particular diagnosis or procedure, many variances may still unavoidably occur. Some key index parameters have strong relationship with variances handling measures of CP. In real world, these problems are highly nonlinear in nature so that it's hard to develop a comprehensive mathematic model. In this paper, a rule extraction approach based on combing hybrid genetic double multi-group cooperative particle swarm optimization algorithm (PSO) and discrete PSO algorithm (named HGDMCPSO/DPSO) is developed to discovery the previously unknown and potentially complicated nonlinear relationship between key parameters and variances handling measures of CP. Then these extracted rules can provide abnormal variances handling warning for medical professionals. Three numerical experiments on Iris of UCI data sets, Wisconsin breast cancer data sets and CP variances data sets of osteosarcoma preoperative chemotherapy are used to validate the proposed method. When compared with the previous researches, the proposed rule extraction algorithm can obtain the high prediction accuracy, less computing time, more stability and easily comprehended by users, thus it is an effective knowledge extraction tool for CP variances handling.

  10. 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.

  11. Estimates of (co)variance components and genetic parameters for growth traits in Sirohi goat.

    Science.gov (United States)

    Gowane, Gopal R; Chopra, Ashish; Prakash, Ved; Arora, A L

    2011-01-01

    Data were collected over a period of 21 years (1988-2008) to estimate (co)variance components for birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), weaning to 6WT (ADG2), and from 6WT to 12WT (ADG3) in Sirohi goats maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India. Analyses were carried out by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. The best model was chosen after testing the improvement of the log-likelihood values. Heritability estimates for BWT, WWT, 6WT, 9WT, 12WT, ADG1, ADG2, and ADG3 were 0.39 ± 0.05, 0.09 ± 0.03, 0.06 ± 0.02, 0.09 ± 0.03, 0.11 ± 0.03, 0.10 ± 0.3, 0.04 ± 0.02, and 0.01 ± 0.01, respectively. For BWT and ADG1, only direct effects were significant. Estimate of maternal permanent environmental effect were important for body weights from weaning to 12WT and also for ADG2 and ADG3. However, direct maternal effects were not significant throughout. Estimate of c (2) were 0.06 ± 0.02, 0.03 ± 0.02, 0.06 ± 0.02, 0.05 ± 0.02, 0.02 ± 0.02, and 0.02 ± 0.02 for 3WT, 6WT, 9WT, 12WT, ADG2, and ADG3, respectively. The estimated repeatabilities across years of ewe effects on kid body weights were 0.10, 0.08, 0.05, 0.08, and 0.08 at birth, weaning, 6, 9, and 12 months of age, respectively. Results suggest possibility of modest rate of genetic progress for body weight traits and ADG1 through selection, whereas only slow progress will be possible for post-weaning gain. Genetic and phenotypic correlations between body weight traits were high and positive. High genetic correlation between 6WT and 9WT suggests that selection of animals at 6 months can be carried out instead of present practice of selection at 9 months.

  12. Genetic (co)variance of rainbow trout (Oncorhynchus mykiss) body weight and its uniformity across production environments.

    Science.gov (United States)

    Sae-Lim, Panya; Kause, Antti; Janhunen, Matti; Vehviläinen, Harri; Koskinen, Heikki; Gjerde, Bjarne; Lillehammer, Marie; Mulder, Han A

    2015-05-19

    When rainbow trout from a single breeding program are introduced into various production environments, genotype-by-environment (GxE) interaction may occur. Although growth and its uniformity are two of the most important traits for trout producers worldwide, GxE interaction on uniformity of growth has not been studied. Our objectives were to quantify the genetic variance in body weight (BW) and its uniformity and the genetic correlation (rg) between these traits, and to investigate the degree of GxE interaction on uniformity of BW in breeding (BE) and production (PE) environments using double hierarchical generalized linear models. Log-transformed data were also used to investigate whether the genetic variance in uniformity of BW, GxE interaction on uniformity of BW, and rg between BW and its uniformity were influenced by a scale effect. Although heritability estimates for uniformity of BW were low and of similar magnitude in BE (0.014) and PE (0.012), the corresponding coefficients of genetic variation reached 19 and 21%, which indicated a high potential for response to selection. The genetic re-ranking for uniformity of BW (rg = 0.56) between BE and PE was moderate but greater after log-transformation, as expressed by the low rg (-0.08) between uniformity in BE and PE, which indicated independent genetic rankings for uniformity in the two environments when the scale effect was accounted for. The rg between BW and its uniformity were 0.30 for BE and 0.79 for PE but with log-transformed BW, these values switched to -0.83 and -0.62, respectively. Genetic variance exists for uniformity of BW in both environments but its low heritability implies that a large number of relatives are needed to reach even moderate accuracy of selection. GxE interaction on uniformity is present for both environments and sib-testing in PE is recommended when the aim is to improve uniformity across environments. Positive and negative rg between BW and its uniformity estimated with original

  13. Speeding Up Microevolution: The Effects of Increasing Temperature on Selection and Genetic Variance in a Wild Bird Population

    Science.gov (United States)

    Husby, Arild; Visser, Marcel E.; Kruuk, Loeske E. B.

    2011-01-01

    The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental conditions, very little is known about the extent to which they may covary in response to environmental heterogeneity. Here we show that, in a wild population of great tits (Parus major), the strength of the directional selection gradients on timing of breeding increased with increasing spring temperatures, and that genotype-by-environment interactions also predicted an increase in additive genetic variance, and heritability, of timing of breeding with increasing spring temperature. Consequently, we therefore tested for an association between the annual selection gradients and levels of additive genetic variance expressed each year; this association was positive, but non-significant. However, there was a significant positive association between the annual selection differentials and the corresponding heritability. Such associations could potentially speed up the rate of micro-evolution and offer a largely ignored mechanism by which natural populations may adapt to environmental changes. PMID:21408101

  14. Shared genetic variance between the features of the metabolic syndrome: Heritability studies

    NARCIS (Netherlands)

    Povel, C.M.; Boer, J.M.A.; Feskens, E.J.M.

    2011-01-01

    Heritability estimates of MetS range from approximately 10%–30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation

  15. Normal linear models with genetically structured residual variance heterogeneity: a case study

    DEFF Research Database (Denmark)

    Sorensen, Daniel; Waagepetersen, Rasmus Plenge

    2003-01-01

    Normal mixed models with different levels of heterogeneity in the residual variance are fitted to pig litter size data. Exploratory analysis and model assessment is based on examination of various posterior predictive distributions. Comparisons based on Bayes factors and related criteria favour...

  16. A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference Genetics Selection Evolution 2010, 42:29

    DEFF Research Database (Denmark)

    Ødegård, Jørgen; Meuwissen, Theo HE; Heringstad, Bjørg

    2010-01-01

    Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where...... individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (co)variance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative......" or "non-informative" with respect to genetic (co)variance components. The "non-informative" individuals are characterized by their Mendelian sampling deviations (deviance from the mid-parent mean) being completely confounded with a single residual on the underlying liability scale. For threshold models...

  17. Stability of genetic variance and covariance for reproductive characters in the face of climate change in a wild bird population.

    Science.gov (United States)

    Garant, Dany; Hadfield, Jarrod D; Kruuk, Loeske E B; Sheldon, Ben C

    2008-01-01

    Global warming has had numerous effects on populations of animals and plants, with many species in temperate regions experiencing environmental change at unprecedented rates. Populations with low potential for adaptive evolutionary change and plasticity will have little chance of persistence in the face of environmental change. Assessment of the potential for adaptive evolution requires the estimation of quantitative genetic parameters, but it is as yet unclear what impact, if any, global warming will have on the expression of genetic variances and covariances. Here we assess the impact of a changing climate on the genetic architecture underlying three reproductive traits in a wild bird population. We use a large, long-term, data set collected on great tits (Parus major) in Wytham Woods, Oxford, and an 'animal model' approach to quantify the heritability of, and genetic correlations among, laying date, clutch size and egg mass during two periods with contrasting temperature conditions over a 40-year period (1965-1988 [cooler] vs. 1989-2004 [warmer]). We found significant additive genetic variance and heritability for all traits under both temperature regimes. We also found significant negative genetic covariances and correlations between clutch size and egg weight during both periods, and among laying date and clutch size in the colder years only. The overall G matrix comparison among periods, however, showed only a minor difference among periods, thus suggesting that genotype by environment interactions are negligible in this context. Our results therefore suggest that despite substantial changes in temperature and in mean laying date phenotype over the last decades, and despite the large sample sizes available, we are unable to detect any significant change in the genetic architecture of the reproductive traits studied.

  18. Genetic variance and covariance components related to intra- and interpopulation recurrent selection in maize (Zea mays L.

    Directory of Open Access Journals (Sweden)

    Arias Carlos Alberto Arrabal

    1998-01-01

    Full Text Available New genetic variance and covariance components related to intra- and interpopulational recurrent selection methods have been theoretically developed by Souza Jr. (Rev. Bras. Genet. 16: 91-105, 1993 to explain the failure of these methods to concomitantly develop hybrid and per se populations. Intra- and interpopulation half-sib progenies of 100 genotypes were sampled from maize (Zea mays L. populations BR-106 and BR-105 to estimate variance and covariance components and to compare the expected responses to reciprocal (RRS, intrapopulational (HSS, and modified (MRS recurrent selection in interpopulation hybrid, populations per se, and to determine heterosis. Four sets of 100 progenies, two intra- and two interpopulational, were evaluated in partially balanced 10 x 10 lattices arranged in split-blocks with two replications in two years (1991/92 and 1992/93 and two locations in Piracicaba, SP. Data for ear weight, plant and ear height, and ear by plant height ratio were recorded. Populations and interpopulation crosses were high yielding and showed high breeding potential for production of hybrids from inbred lines. Mid parent and the highest parent heterosis were relatively high, but lower than values reported for these populations under other environmental conditions. Additive variance estimates of populations per se and interpopulation crosses confirmed the high potential of these materials. The magnitude of the variance estimates for the deviations from intra- and interpopulation additive effects ( for BR-106 and for BR-105 and covariance between additive effects with these deviations ( for BR-106 and for BR-105 indicated that these new components can significantly influence the effectiveness of breeding methods. Genetic component estimates for BR-105 had relatively small errors, with negative for all traits. Estimates of and had relatively larger errors for BR-106. The MRS method was more effective than the RRS and HSS methods in producing

  19. Who is afraid of math? Two sources of genetic variance for mathematical anxiety.

    Science.gov (United States)

    Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W; Lyons, Ian M; Petrill, Stephen A

    2014-09-01

    Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving and achievement. This study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and nonfamilial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics and may extend to other areas of academic achievement. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

  20. Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety

    Science.gov (United States)

    Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A.; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W.; Lyons, Ian M.; Petrill, Stephen A.

    2015-01-01

    Background Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem-solving and achievement. The present study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Methods Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Results Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and non-familial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. Conclusions The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics, and may extend to other areas of academic achievement. PMID:24611799

  1. Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

    Science.gov (United States)

    Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

    2015-02-09

    Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.

  2. Increased genetic variance of BMI with a higher prevalence of obesity

    DEFF Research Database (Denmark)

    Rokholm, Benjamin; Silventoinen, Karri; Ängquist, Lars

    2011-01-01

    There is no doubt that the dramatic worldwide increase in obesity prevalence is due to changes in environmental factors. However, twin studies suggest that genetic differences are responsible for the major part of the variation in body mass index (BMI) and other measures of body fatness within...... populations. Several recent studies suggest that the genetic effects on adiposity may be stronger when combined with presumed risk factors for obesity. We tested the hypothesis that a higher prevalence of obesity and overweight and a higher BMI mean is associated with a larger genetic variation in BMI....

  3. BDNF contributes to the genetic variance of milk fat yield in German Holstein cattle

    Directory of Open Access Journals (Sweden)

    Lea G. Zielke

    2011-04-01

    Full Text Available AbstractThe gene encoding the brain derived neurotrophic factor (BDNF has been repeatedly associated with human obesity. As such, it could also contribute to the regulation of energy partitioning and the amount of secreted milk fat during lactation, which plays an important role in milk production in dairy cattle. Therefore, we performed an association study using estimated breeding values of bulls and yield deviations of German Holstein dairy cattle to test the effect of BDNF on milk fat yield. A highly significant effect (corrected p-value =3.362 x10-4 was identified for an SNP 168 kb up-stream of the BDNF transcription start. The association tests provided evidence for an additive allele effect of 5.13 kg of fat per lactation on the estimated breeding value for milk fat yield in bulls and 6.80 kg of fat of the own production performance in cows explaining 1.72% and 0.60% of the phenotypic variance in the analysed populations, respectively. The analyses of bulls and cows consistently showed three haplotype groups that differed significantly from each other, suggesting at least two different mutations in the BDNF-region affecting the milk fat yield. The fat yield increasing alleles also had low but significant positive effects on protein and total milk yield which suggests a general role of the BDNF-region in energy partitioning, rather than a specific regulation of fat synthesis. The results obtained in dairy cattle suggest similar effects of BDNF on milk composition in other species, including man.

  4. [Genetic variance of duck preproinsulin gene and its correlations to the traits of carcasses].

    Science.gov (United States)

    Kong, Xiang-Jie; Liu, Xiao-Lin; Wu, Yan; Wang, Jie

    2008-06-01

    Genetic polymorphisms of exon 2 and partial intron of preproinsulin gene were studied in Peking duck and Cherry Valley duck by PCR-SSCP and DNA sequencing technologies. Two single nucleotide mutations, T179C and C195T, were found, respectively. chi2 test reflects that the tested population of Peking duck and Cherry Valley duck were in the Hardy-Weinberg equilibrium state (P>0.05). The relationships between SNPs and the traits of carcasses were analyzed by the least square analysis, which showed that the genotype BB in three lines of Peking duck was significantly higher in carcass weight, carcass net weight and breast muscle weight than AA and BB (P<0.01) and significantly higher in leg muscle weight and sebum weight than AB (P<0.01). In addition, the genotype AA was significantly greater than AB in sebum rate (P<0.01) and carcass net weight (P<0.05), respectively. However, for Cherry Valley duck, only the genotype AB was significantly higher than AA in sebum weight and abdomen fat weight (P<0.05). The results indicated that there was significant correlation between the genetic polymorphisms of preproinsulin gene and the traits of duck carcasses and the allele B was valuable for increasing the carcass weight and breast muscle weight.

  5. Heritability of blood pressure traits and the genetic contribution to blood pressure variance explained by four blood-pressure-related genes.

    NARCIS (Netherlands)

    Rijn, M.J. van; Schut, A.F.; Aulchenko, Y.S.; Deinum, J.; Sayed-Tabatabaei, F.A.; Yazdanpanah, M.; Isaacs, A.; Axenovich, T.I.; Zorkoltseva, I.V.; Zillikens, M.C.; Pols, H.A.; Witteman, J.C.; Oostra, B.A.; Duijn, C.M. van

    2007-01-01

    OBJECTIVE: To study the heritability of four blood pressure traits and the proportion of variance explained by four blood-pressure-related genes. METHODS: All participants are members of an extended pedigree from a Dutch genetically isolated population. Heritability and genetic correlations of systo

  6. Heritability of blood pressure traits and the genetic contribution to blood pressure variance explained by four blood-pressure-related genes.

    NARCIS (Netherlands)

    Rijn, M.J. van; Schut, A.F.; Aulchenko, Y.S.; Deinum, J.; Sayed-Tabatabaei, F.A.; Yazdanpanah, M.; Isaacs, A.; Axenovich, T.I.; Zorkoltseva, I.V.; Zillikens, M.C.; Pols, H.A.; Witteman, J.C.; Oostra, B.A.; Duijn, C.M. van

    2007-01-01

    OBJECTIVE: To study the heritability of four blood pressure traits and the proportion of variance explained by four blood-pressure-related genes. METHODS: All participants are members of an extended pedigree from a Dutch genetically isolated population. Heritability and genetic correlations of

  7. Temporal Genetic Variance and Propagule-Driven Genetic Structure Characterize Naturalized Rainbow Trout (Oncorhynchus mykiss) from a Patagonian Lake Impacted by Trout Farming

    Science.gov (United States)

    Seeb, Lisa W.; Seeb, James E.; Arismendi, Ivan; Hernández, Cristián E.; Gajardo, Gonzalo; Galleguillos, Ricardo; Cádiz, Maria I.; Musleh, Selim S.

    2015-01-01

    Knowledge about the genetic underpinnings of invasions—a theme addressed by invasion genetics as a discipline—is still scarce amid well documented ecological impacts of non-native species on ecosystems of Patagonia in South America. One of the most invasive species in Patagonia’s freshwater systems and elsewhere is rainbow trout (Oncorhynchus mykiss). This species was introduced to Chile during the early twentieth century for stocking and promoting recreational fishing; during the late twentieth century was reintroduced for farming purposes and is now naturalized. We used population- and individual-based inference from single nucleotide polymorphisms (SNPs) to illuminate three objectives related to the establishment and naturalization of Rainbow Trout in Lake Llanquihue. This lake has been intensively used for trout farming during the last three decades. Our results emanate from samples collected from five inlet streams over two seasons, winter and spring. First, we found that significant intra- population (temporal) genetic variance was greater than inter-population (spatial) genetic variance, downplaying the importance of spatial divergence during the process of naturalization. Allele frequency differences between cohorts, consistent with variation in fish length between spring and winter collections, might explain temporal genetic differences. Second, individual-based Bayesian clustering suggested that genetic structure within Lake Llanquihue was largely driven by putative farm propagules found at one single stream during spring, but not in winter. This suggests that farm broodstock might migrate upstream to breed during spring at that particular stream. It is unclear whether interbreeding has occurred between “pure” naturalized and farm trout in this and other streams. Third, estimates of the annual number of breeders (Nb) were below 73 in half of the collections, suggestive of genetically small and recently founded populations that might experience

  8. Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

    Science.gov (United States)

    Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

    2015-11-22

    Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. © 2015 The Author(s).

  9. Genetic and environmental variance and covariance parameters for some reproductive traits of Holstein and Jersey cattle in Antioquia (Colombia

    Directory of Open Access Journals (Sweden)

    Juan Carlos Zambrano

    2014-03-01

    Full Text Available The objective of this study was to estimate the genetic, phenotypic and environmental parameters for calving interval (CI, days open (DO, number of services per conception (NSC and conception rate (CR in Holstein and Jersey cattle in Antioquia (Colombia. Variance and covariance component estimates were obtained by an animal model that was solved using the derivative-free restricted maximum likelihood method. The means and standard deviations for CI, DO, NSC and CR were: 430.32±77.93 days, 127.15±76.96 days, 1.58±1.03 services per conception and 79.88±28.66% in Holstein cattle, and 409.33±86.48 days, 125.62±86.09 days, 1.48±0.98 services per conception and 84.08±27.23% in Jersey cattle, respectively. The heritability estimates (standard errors were: 0.088(0.037, 0.082(0.037, 0.040(0.025 and 0.030(0.026 in Holstein cattle and 0.072(0.098, 0.090(0.104, 0.093(0.097 and 0.147(0.117 in Jersey cattle, respectively. The results show that the genetic, phenotypic and permanent environmental correlations in the two evaluated breeds were favorable for CI × DO, CI × NSC and DO × NSC, but not for CI × CR, DO × CR and NSC × CR. Genetic and permanent environmental correlations were high in most cases in Holstein cattle, whereas in Jersey cattle they were moderate. In contrast, phenotypic correlations were very low in both breeds, except for CI × DO and NSC × CR, which were high. Overall, the genetic component found was very low (<8% in both evaluated breeds and this implies that their selection would take long time and that a good practical management of the herd will be essential in order to improve the reproductive performance.

  10. Genetic (co)variances and breeding value estimation of Gompertz growth curve parameters in Finnish Yorkshire boars, gilts and barrows.

    Science.gov (United States)

    Koivula, M; Sevón-Aimonen, M-L; Strandén, I; Matilainen, K; Serenius, T; Stalder, K J; Mäntysaari, E A

    2008-06-01

    This paper's objectives were to estimate the genetic (co)variance components of the Gompertz growth curve parameters and to evaluate the relationship of estimated breeding values (EBV) based on average daily gain (ADG) and Gompertz growth curves. Finnish Yorkshire central test station performance data was obtained from the Faba Breeding (Vantaa, Finland). The final data set included 121,488 weight records from 10,111 pigs. Heritability estimates for the Gompertz growth parameters mature weight (alpha), logarithm of mature weight to birth weight ratio (beta) and maturation rate (kappa) were 0.44, 0.55 and 0.31, respectively. Genotypic and phenotypic correlations between the growth curve parameters were high and mainly negative. The only positive relationship was found between alpha and beta. Pearson and Spearman rank correlation coefficients between EBV for ADG and daily gain calculated from Gompertz growth curves were 0.79. The Spearman rank correlation between the sire EBV for ADG and Gompertz growth curve parameter-based ADG for all sires with at least 15 progeny was 0.86. Growth curves differ significantly between individuals and this information could be utilized for selection purposes when improving growth rate in pigs.

  11. A comparison of identity-by-descent and identity-by-state matrices that are used for genetic evaluation and estimation of variance components.

    Science.gov (United States)

    Fernando, R L; Cheng, H; Sun, X; Garrick, D J

    2017-06-01

    The genetic covariance matrix conditional on pedigree is proportional to the pedigree-based additive relationship matrix (PARM), which is twice the matrix of identity-by-descent (IBD) probabilities. In genomic prediction, IBD probabilities in the PARM, which are expected genetic similarities between relatives that are derived from the pedigree, are substituted by realized similarities that are derived from genotypes to obtain a genomic additive relationship matrix (GARM). Different definitions of similarity lead to different GARMs, and two commonly used GARMS are the matrix G, which is based on an allele substitution effect model, and the matrix T, which is based on an allele effect model. We show that although the two matrices T and G are not proportional, they give identical predictions of differences between breeding values. When genomic information is used for variance component estimation, the GARM Gx is computed from genotype covariates that have been standardized to have unit variance. That approach is equivalent to fitting a random regression model using the same standardized covariates. We show that under Hardy-Weinberg and linkage equilibria (LE) that the genetic variance is kσγ2, where σγ2 is the variance of a randomly sampled element from the vector of k substitution effects. However, if linkage disequilibrium (LD) has been generated through selection, covariances between genotypes at different loci will be negative, and therefore, the additive genetic variance will be lower than kσγ2. When the GARM Gx is assumed to be proportional to the genetic covariance matrix, the parameter being estimated is kσγ2. We have demonstrated by simulation that kσγ2 overestimates the additive genetic variance when LD is generated by selection. We argue that unlike the PARM, GARMs are not proportional to a genetic covariance matrix conditional on the observed causal genotypes. The objective here is to recognize the difference between these covariance matrices and

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

    National Research Council Canada - National Science Library

    John B Holmes; Ken G Dodds; Michael A Lee

    2017-01-01

    .... 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...

  13. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

    NARCIS (Netherlands)

    Mulder, H.A.; Ronnegard, L.; Veerkamp, R.F.; Strandberg, E.

    2013-01-01

    Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The

  14. Variance estimation between different body measurements at the females population from Romanian Mioritic Shepherd Dog breed, to develop a genetic improvement program

    Directory of Open Access Journals (Sweden)

    Dorel Dronca

    2016-05-01

    Full Text Available Romanian Mioritic Shepherd Dog, was selected from a natural population breed in Carpathian Mountains. The aim of this paper was to estimate variance at 12 body measurements using 23 females from Romanian Mioritic Shepherd Dog breed. The animals were registered with the Romanian Mioritic Association Club from Romania. In order to develop a genetic improvement program at this effective of 23 females from Romanian Sheperd Dog breed, found in evidence of Romanian Mioritic Association Club from Romania, should be considered the following conclusions on variance those 12 characters studied in this paper, respectively, there is a large variance for the height at the middle back, the height at the croup, the height at the base of the tail, the width of the croup, the length of the tail, the depth of the thorax, the thorax perimeter, the height of the elbow and  for the height at the withers, the body length and the height at the hocks, the variance is middle.

  15. Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

    Science.gov (United States)

    Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

    2015-03-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

  16. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    DEFF Research Database (Denmark)

    Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage;

    2012-01-01

    Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total...... genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition...... of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

  17. FADS2 Genetic Variance in Combination with Fatty Acid Intake Might Alter Composition of the Fatty Acids in Brain.

    Directory of Open Access Journals (Sweden)

    Thais S Rizzi

    Full Text Available Multiple lines of evidence suggest that fatty acids (FA play an important role in cognitive function. However, little is known about the functional genetic pathways involved in cognition. The main goals of this study were to replicate previously reported interaction effects between breast feeding (BF and FA desaturase (FADS genetic variation on IQ and to investigate the possible mechanisms by which these variants might moderate BF effect, focusing on brain expression. Using a sample of 534 twins, we observed a trend in the moderation of BF effects on IQ by FADS2 variation. In addition, we made use of publicly available gene expression databases from both humans (193 and mice (93 and showed that FADS2 variants also correlate with FADS1 brain expression (P-value<1.1E-03. Our results provide novel clues for the understanding of the genetic mechanisms regulating FA brain expression and improve the current knowledge of the FADS moderation effect on cognition.

  18. Variance Components and Genetic Parameters Estimated for Fat and Protein Content in Individual Months of Lactation: The Case of Tsigai Sheep.

    Science.gov (United States)

    Oravcová, Marta

    2016-02-01

    The objective of this study was to assess variance components and genetic parameters for fat and protein content in Tsigai sheep using multivariate animal models in which fat and protein content in individual months of lactation were treated as different traits, and univariate models in which fat and protein content were treated as repeated measures of the same traits. Test day measurements were taken between the second and the seventh month of lactation. The fixed effects were lactation number, litter size and days in milk. The random effects were animal genetic effect and permanent environmental effect of ewe. The effect of flock-year-month of test day measurement was fitted either as a fixed (FYM) or random (fym) effect. Heritabilities for fat content were estimated between 0.06 and 0.17 (FYM fitted) and between 0.06 and 0.11 (fym fitted). Heritabilities for protein content were estimated between 0.15 and 0.23 (FYM fitted) and between 0.10 and 0.18 (fym fitted). For fat content, variance ratios of permanent environmental effect of ewe were estimated between 0.04 and 0.11 (FYM fitted) and between 0.02 and 0.06 (fym fitted). For protein content, variance ratios of permanent environmental effect of ewe were estimated between 0.13 and 0.20 (FYM fitted) and between 0.08 and 0.12 (fym fitted). The proportion of phenotypic variance explained by fym effect ranged from 0.39 to 0.43 for fat content and from 0.25 to 0.36 for protein content. Genetic correlations between individual months of lactation ranged from 0.74 to 0.99 (fat content) and from 0.64 to 0.99 (protein content). Fat content heritabilities estimated with univariate animal models roughly corresponded with heritability estimates from multivariate models: 0.13 (FYM fitted) and 0.07 (fym fitted). Protein content heritabilities estimated with univariate animal models also corresponded with heritability estimates from multivariate models: 0.18 (FYM fitted) and 0.13 (fym fitted).

  19. FADS2 Genetic Variance in Combination with Fatty Acid Intake Might Alter Composition of the Fatty Acids in Brain

    NARCIS (Netherlands)

    T.S. Rizzi (Thais); S. van der Sluis (Sophie); C. Derom (Catherine); E. Thiery (Evert); R.E. Kesteren (Ronald); N. Jacobs (Nele); S. van Gestel (Sofie); R. Vlietinck (Robert); M. Verhage (Matthijs); P. Heutink (Peter); D. Posthuma (Danielle)

    2013-01-01

    textabstractMultiple lines of evidence suggest that fatty acids (FA) play an important role in cognitive function. However, little is known about the functional genetic pathways involved in cognition. The main goals of this study were to replicate previously reported interaction effects between brea

  20. Multi-period fuzzy mean-semi variance portfolio selection problem with transaction cost and minimum transaction lots using genetic algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Barati

    2016-04-01

    Full Text Available Multi-period models of portfolio selection have been developed in the literature with respect to certain assumptions. In this study, for the first time, the portfolio selection problem has been modeled based on mean-semi variance with transaction cost and minimum transaction lots considering functional constraints and fuzzy parameters. Functional constraints such as transaction cost and minimum transaction lots were included. In addition, the returns on assets parameters were considered as trapezoidal fuzzy numbers. An efficient genetic algorithm (GA was designed, results were analyzed using numerical instances and sensitivity analysis were executed. In the numerical study, the problem was solved based on the presence or absence of each mode of constraints including transaction costs and minimum transaction lots. In addition, with the use of sensitivity analysis, the results of the model were presented with the variations of minimum expected rate of programming periods.

  1. Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Bharat Merino sheep.

    Science.gov (United States)

    Gowane, G R; Chopra, A; Prince, L L L; Paswan, C; Arora, A L

    2010-03-01

    (Co)variance components and genetic parameters of weight at birth (BWT), weaning (3WT), 6, 9 and 12 months of age (6WT, 9WT and 12WT, respectively) and first greasy fleece weight (GFW) of Bharat Merino sheep, maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 10 years (1998 to 2007). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for BWT, 3WT, 6WT, 9WT and 12WT and first GFW were 0.05 ± 0.03, 0.04 ± 0.02, 0.00, 0.03 ± 0.03, 0.09 ± 0.05 and 0.05 ± 0.03, respectively. There was no evidence for the maternal genetic effect on the traits under study. Maternal permanent environmental effect contributed 19% for BWT and 6% to 11% from 3WT to 9WT and 11% for first GFW. Maternal permanent environmental effect on the post-3WT was a carryover effect of maternal influences during pre-weaning age. A low rate of genetic progress seems possible in the flock through selection. Direct genetic correlations between body weight traits were positive and ranged from 0.36 between BWT and 6WT to 0.94 between 3WT and 6WT and between 6WT and 12WT. Genetic correlations of 3WT with 6WT, 9WT and 12WT were high and positive (0.94, 0.93 and 0.93, respectively), suggesting that genetic gain in post-3WT will be maintained if selection age is reduced to 3 months. The genetic correlations of GFW with live weights were 0.01, 0.16, 0.18, 0.40 and 0.32 for BWT, 3WT, 6WT, 9WT and 12WT, respectively. Correlations of permanent environmental effects of the dam across different traits were high and positive for all the traits (0.45 to 0.98).

  2. Genetic correlations and little genetic variance for reaction norms may limit potential for adaptation to pollution by ionic and nanoparticulate silver in a whitefish (Salmonidae).

    Science.gov (United States)

    Clark, Emily S; Pompini, Manuel; Uppal, Anshu; Wedekind, Claus

    2016-05-01

    For natural populations to adapt to anthropogenic threats, heritable variation must persist in tolerance traits. Silver nanoparticles, the most widely used engineered nanoparticles, are expected to increase in concentrations in freshwaters. Little is known about how these particles affect wild populations, and whether genetic variation persists in tolerance to permit rapid evolutionary responses. We sampled wild adult whitefish and crossed them in vitro full factorially. In total, 2896 singly raised embryos of 48 families were exposed to two concentrations (0.5 μg/L; 100 μg/L) of differently sized silver nanoparticles or ions (silver nitrate). These doses were not lethal; yet higher concentrations prompted embryos to hatch earlier and at a smaller size. The induced hatching did not vary with nanoparticle size and was stronger in the silver nitrate group. Additive genetic variation for hatching time was significant across all treatments, with no apparent environmental dependencies. No genetic variation was found for hatching plasticity. We found some treatment-dependent heritable variation for larval length and yolk volume, and one instance of additive genetic variation for the reaction norm on length at hatching. Our assessment suggests that the effects of silver exposure on additive genetic variation vary according to trait and silver source. While the long-term fitness consequences of low-level silver exposure on whitefish embryos must be further investigated to determine whether it is, in fact, detrimental, our results suggest that the evolutionary potential for adaptation to these types of pollutants may be low.

  3. Locus BoLA-DRB3 is just an ordinary site of the polygene when explaining genetic variance of somatic cell count and milk yield.

    Science.gov (United States)

    Oprzadek, Jolanta; Sender, Grazyna; Pawlik, Adrianna; Lukaszewicz, Marek

    2015-11-01

    The study aimed at clarifying the problem of the hitherto contradictory results regarding usefulness of BoLA-DRB3 locus as a marker in selection against mastitis and for milk yield. Treating the BoLA-DRB3 locus effect as random was proposed in place of considering it fixed. Somatic cell counts and milk yields recorded monthly on a test day (22,424) of 619 Polish Holstein cows genotyped for BoLA-DRB3 were analysed with an animal model including a random effect for genotype at this locus. The BoLA-DRB3 alleles were defined as restriction patterns obtained with three endonucleases. Two alternative BoLA-DRB3 additive genotype (co)variance structures were constructed for 161 genotypes recorded. One was based on the allelic similarity of the genotypes resulting in element values of 0 (no common allele), 0.5 (one allele in common), and 1 (diagonal). The other considered restriction site similarity (up to 3 in 1 allele) giving element values of 0 (no common restriction sites) and then increasingly in steps of 1/6 up to 6/6 (diagonal), where the numerator represents the number of common sites between genotypes. The DRB3 variance component for the natural logarithm of somatic cell count did not exceed 0.006 of the polygenic additive component or 0.003 for milk yield. Hence, unless we fail to detect the causative site or to properly define traits being the projection of a site, the effect of the genotype at the BoLA-DRB3 locus does not explain variation in somatic cell count and milk yield at a degree expected of a genetic marker.

  4. Variance, genetic control and spatial phenotypic plasticity of morphological and phenological traits in Prunus spinosa and its large fruited forms (P. x fruticans

    Directory of Open Access Journals (Sweden)

    Kristine Vander Mijnsbrugge

    2016-11-01

    diminished at the growth site with the shortest growing season while interestingly, the leaf width was enlarged. Leaf size traits appeared more plastic on the long shoots compared to the short shoots, although partitioning of variance did not display a lesser genetic

  5. Previous estimates of mitochondrial DNA mutation level variance did not account for sampling error: comparing the mtDNA genetic bottleneck in mice and humans.

    Science.gov (United States)

    Wonnapinij, Passorn; Chinnery, Patrick F; Samuels, David C

    2010-04-09

    In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference.

  6. Structure and stability of genetic variance-covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three-spined stickleback.

    Science.gov (United States)

    Siren, J; Ovaskainen, O; Merilä, J

    2017-07-26

    The genetic variance-covariance matrix (G) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G-matrices is limited for two reasons. First, phenotypes are high-dimensional, whereas traditional statistical methods are tuned to estimate and analyse low-dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high-dimensional G-matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half-sib breeding design of three-spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low-temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability-as well as the similarity among G-matrices-may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G-matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G, they also illustrate that by enabling the estimation of large G-matrices, the BSFG method can improve predicted evolutionary responses to selection. © 2017 John Wiley & Sons Ltd.

  7. Downside Variance Risk Premium

    OpenAIRE

    Feunou, Bruno; Jahan-Parvar, Mohammad R.; Okou, Cédric

    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...

  8. 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...

  9. 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...

  10. 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…

  11. 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...

  12. Evidence that BMI and type 2 diabetes share only a minor fraction of genetic variance: a follow-up study of 23,585 monozygotic and dizygotic twins from the Finnish Twin Cohort Study.

    Science.gov (United States)

    Lehtovirta, M; Pietiläinen, K H; Levälahti, E; Heikkilä, K; Groop, L; Silventoinen, K; Koskenvuo, M; Kaprio, J

    2010-07-01

    We investigated whether BMI predicts type 2 diabetes in twins and to what extent that is explained by common genetic factors. This was a population-based twin cohort study. Monozygotic (n = 4,076) and dizygotic (n = 9,109) non-diabetic twin pairs born before 1958 answered a questionnaire in 1975, from which BMI was obtained. Information on incident cases of diabetes was obtained by linkage to nationwide registers until 2005. Altogether, 1,332 twins (6.3% of men, 5.1% of women) developed type 2 diabetes. The HR for type 2 diabetes increased monotonically with a mean of 1.22 (95% CI 1.20-1.24) per BMI unit and of 1.97 (95% CI 1.87-2.08) per SD of BMI. The HRs for lean, overweight, obese and morbidly obese participants were 0.59, 2.96, 6.80 and 13.64 as compared with normal weight participants. Model heritability estimates for bivariate variance due to an additive genetic component and non-shared environmental component were 75% (men) and 71% (women) for BMI, and 73% and 64%, respectively for type 2 diabetes. The correlations between genetic variance components (r (g)) indicated that one fifth of the covariance of BMI and type 2 diabetes was due to shared genetic influences. Although the mean monozygotic concordance for type 2 diabetes was approximately twice the dizygotic one, age of onset of diabetes within twin pair members varied greatly, irrespective of zygosity. A 28-year follow-up of adult Finnish twins showed that despite high trait heritability estimates, only a fraction of covariation in BMI and incident type 2 diabetes was of genetic origin.

  13. Generalized analysis of molecular variance.

    Directory of Open Access Journals (Sweden)

    Caroline M Nievergelt

    2007-04-01

    Full Text Available Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA, requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by

  14. Temporal change in the genetic structure between and within cohorts of a marine fish, Diplodus sargus, induced by a large variance in individual reproductive success.

    Science.gov (United States)

    Planes, S; Lenfant, P

    2002-08-01

    Temporal changes at 16 allozyme loci in the Diplodus sargus population of Banyuls-sur-Mer (Mediterranean Sea, France) were monitored. Temporal genetic variation within a single population was examined over two temporal scales: (i) among three year-classes sampled at the same age, and (ii) within a single year-class sampled three times over a two-year period. We observed a significant change in the genotypic structure within the same cohort during the first two years following settlement and before recruitment into the adult population. In addition, comparison of year-classes showed that cohorts differed significantly one year after settlement, whereas they became similar later on before recruitment into the adult population. The observed changes in the genetic structure within and between year-classes may be the result of complex selective processes or genetic drift. Linkage disequilibrium and genetic relatedness data suggest that these changes are due to large variation in reproductive success, followed by homogenization through adult movement. Overall, these results demonstrated a rapid genetic change within a population.

  15. Variance of genetic parameters for gas accumulations in the Rotliegende of the Western Altmark; Varianz lagerstaettengenetischer Parameter im Rotliegenden der westlichen Altmark

    Energy Technology Data Exchange (ETDEWEB)

    Schumacher, K.H. [Erdoel-Erdgas Gommern GmbH, Gommern (Germany); May, F. [Erdoel-Erdgas Gommern GmbH, Gommern (Germany)

    1993-12-31

    The gas fields of the western Altmark show a distinct zonal variance of gas- and isotope-geochemical and lithological parameters. The diapir-like distribution of methane contents and isotopes ratios gives information not only on the role played by the N-S faults associated with the Rotliegende rifting in providing gas-migration paths, but also on special aspects of the migration process. (orig.) [Deutsch] In den Lagerstaetten der westlichen Altmark tritt eine ausgepraegte zonale Varianz erdgas- und isotopengeochemischer sowie lithologischer Parameter auf. An Hand diapirartiger Erscheinungsbilder der Methangehalts- und Isotopenverteilungen werden neben der Rolle der N-S-gerichteten Bruchstoerungen des Rotliegend-Riftings fuer die Erdgaszufuhr zugleich Besonderheiten des Migrationsablaufes deutlich. (orig.)

  16. Variational bayesian method of estimating variance components.

    Science.gov (United States)

    Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi

    2016-07-01

    We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.

  17. Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle.

    Science.gov (United States)

    Retallick, K J; Bormann, J M; Weaber, R L; MacNeil, M D; Bradford, H L; Freetly, H C; Hales, K E; Moser, D W; Snelling, W M; Thallman, R M; Kuehn, L A

    2017-04-01

    Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.

  18. 立枯丝核菌遗传多样性的研究方法%Methodology in Researching of Genetic Variance of Rhizoctonia solani

    Institute of Scientific and Technical Information of China (English)

    王利红; 姜华; 王艳丽; 孙国昌

    2013-01-01

    Rhizoctonia solani Ktihn is a plant pathogenic fungus with a wide host range and abundant genetic diversity. The study on the genetic diversity of R. solani is a kind of research hotspot. In this paper, we reviewed several techniques widely used in the studies on the genetic diversity of R. solani. We interpreted and described the advantages and disadvantages of each method. Hyphal fusion is a traditional method, which requires the use of a microscope and is time-consuming and labor-intensive. The method for identifying the pattern of isoenzyme is simple, efficient and inexpensive, and has to be associated with other techniques. The fatty acids analysis is easy to be manipulated, and the cost is relatively low, but the method is limited by the strain growth conditions and the way of fatty acid esterified. Many molecular marker methods were used in the research on the genetic diversity of R. solani, each with the pros and cons, by comparison we suggest that the rDNA-ITS is the more appropriate method. The applications of these methods were also discussed in the paper.%立枯丝核菌(Rhizoctonia solani Kühn)是一个集合种,遗传多样性丰富.关于遗传多样性的研究一直是R.solani研究的热点.本文就用于R.solani遗传多样性研究的方法进行了综述.分别解释并阐述了各种方法的优缺点,其中菌丝融合法是研究R.solani遗传多样性的传统方法,该法需借助显微镜且耗时耗力;同工酶法简便、高效、低廉,但常需要与其它方法联用;脂肪酸法操作难度小,价格相对较低,但该法受菌株生长状况和脂肪酸脂化方法的限制;分子标记法方法众多,各有利弊,通过比较发现rDNA-ITS是研究R.solani遗传多样性比较合适的方法.本文还介绍了不同方法在R.solani遗传多样性研究中的具体应用.

  19. Conversations across Meaning Variance

    Science.gov (United States)

    Cordero, Alberto

    2013-01-01

    Progressive interpretations of scientific theories have long been denounced as naive, because of the inescapability of meaning variance. The charge reportedly applies to recent realist moves that focus on theory-parts rather than whole theories. This paper considers the question of what "theory-parts" of epistemic significance (if any) relevantly…

  20. Nominal analysis of "variance".

    Science.gov (United States)

    Weiss, David J

    2009-08-01

    Nominal responses are the natural way for people to report actions or opinions. Because nominal responses do not generate numerical data, they have been underutilized in behavioral research. On those occasions in which nominal responses are elicited, the responses are customarily aggregated over people or trials so that large-sample statistics can be employed. A new analysis is proposed that directly associates differences among responses with particular sources in factorial designs. A pair of nominal responses either matches or does not; when responses do not match, they vary. That analogue to variance is incorporated in the nominal analysis of "variance" (NANOVA) procedure, wherein the proportions of matches associated with sources play the same role as do sums of squares in an ANOVA. The NANOVA table is structured like an ANOVA table. The significance levels of the N ratios formed by comparing proportions are determined by resampling. Fictitious behavioral examples featuring independent groups and repeated measures designs are presented. A Windows program for the analysis is available.

  1. 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...

  2. Variance decomposition of apolipoproteins and lipids in Danish twins

    DEFF Research Database (Denmark)

    Fenger, Mogens; Schousboe, Karoline; Sørensen, Thorkild I A

    2007-01-01

    OBJECTIVE: Twin studies are used extensively to decompose the variance of a trait, mainly to estimate the heritability of the trait. A second purpose of such studies is to estimate to what extent the non-genetic variance is shared or specific to individuals. To a lesser extent the twin studies have...... been used in bivariate or multivariate analysis to elucidate common genetic factors to two or more traits. METHODS AND RESULTS: In the present study the variances of traits related to lipid metabolism is decomposed in a relatively large Danish twin population, including bivariate analysis to detect...

  3. Fixed effects analysis of variance

    CERN Document Server

    Fisher, Lloyd; Birnbaum, Z W; Lukacs, E

    1978-01-01

    Fixed Effects Analysis of Variance covers the mathematical theory of the fixed effects analysis of variance. The book discusses the theoretical ideas and some applications of the analysis of variance. The text then describes topics such as the t-test; two-sample t-test; the k-sample comparison of means (one-way analysis of variance); the balanced two-way factorial design without interaction; estimation and factorial designs; and the Latin square. Confidence sets, simultaneous confidence intervals, and multiple comparisons; orthogonal and nonorthologonal designs; and multiple regression analysi

  4. Statistical inference on variance components

    NARCIS (Netherlands)

    Verdooren, L.R.

    1988-01-01

    In several sciences but especially in animal and plant breeding, the general mixed model with fixed and random effects plays a great role. Statistical inference on variance components means tests of hypotheses about variance components, constructing confidence intervals for them, estimating them,

  5. 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

    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...

  6. Efeitos da Heterogeneidade de Variância Residual entre Grupos de Contemporâneos na Avaliação Genética de Bovinos de Corte Effects of Heterogeneity of Residual Variance among Contemporary Groups on Genetic Evaluation of Beef Cattle

    Directory of Open Access Journals (Sweden)

    Roberto Carvalheiro

    2002-07-01

    Full Text Available O objetivo deste estudo foi investigar, por meio de dados simulados, o efeito da heterogeneidade de variância residual entre grupos de contemporâneos (GC sobre as avaliações genéticas de bovinos de corte, e comparar o uso de uma avaliação genética ponderada (R¹Isigmae² em relação à avaliação que pressupõe homogeneidade de variância (R=Isigmae². A característica estudada foi ganho de peso pós-desmame corrigido para 345 dias, sendo esta simulada com variância fenotípica de 300 kg² e herdabilidade igual a 0,4. A estrutura de um conjunto real de dados foi utilizada para fornecer os GC e os pais referentes às observações de cada animal. Cinco níveis de heterogeneidade de variância residual foram considerados de forma que os componentes de variância fossem, na média, iguais aos da situação de homogeneidade de variância. Na medida em que níveis mais acentuados de heterogeneidade de variância residual foram considerados, os animais foram selecionados dos GC com maior variabilidade, especialmente com pressão de seleção intensa. Em relação à consistência de predição, os produtos e as vacas tiveram seus valores genéticos preditos mais afetados pela heterogeneidade de variância residual do que os touros. O fator de ponderação utilizado reduziu, mas não eliminou o efeito da heterogeneidade de variância. As avaliações genéticas ponderadas apresentaram resultados iguais ou superiores àqueles obtidos pelas avaliações que assumiram homogeneidade de variância. Mesmo quando não necessário, o uso de avaliações ponderadas produziu resultados não inferiores às avaliações que assumiram homogeneidade de variância.The objective of this study was to investigate, via simulated data, the effect of heterogeneity of residual variance among contemporary groups (CG on genetic evaluation of beef cattle, and to compare a weighted genetic evaluation procedure (R¹Isigmae² with one that assumes homogeneity of

  7. Markov bridges, bisection and variance reduction

    DEFF Research Database (Denmark)

    Asmussen, Søren; Hobolth, Asger

    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....... 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...... where the methods of stratification, importance sampling and quasi Monte Carlo are investigated....

  8. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  9. Modelling volatility by variance decomposition

    DEFF Research Database (Denmark)

    Amado, Cristina; Teräsvirta, Timo

    on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns...... illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance....

  10. Revision: Variance Inflation in Regression

    Directory of Open Access Journals (Sweden)

    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.

  11. Genetic variance and breeding values for resistance to a wind-borne disease [Sphaerotheca macularis (Wallr. ex Fr.)] in strawberry (Fragaria x ananassa Duch.) estimated by exploring mixed and spatial models and pedigree information.

    Science.gov (United States)

    Davik, Jahn; Honne, Bjørn Ivar

    2005-07-01

    A mixed model approach was used to estimate variance components and heritabilities for resistance to powdery mildew, a wind-borne disease in strawberry. In order to improve precision in the statistical computations, spatial error control effects were included to account for systematic environmental variations in the large field trials. Pedigree information was included where feasible. Seedling families obtained from an incomplete 63-by-63 diallel cross were grown at six locations and scored subjectively for mildew attack three times during the growing season. The 63 parents included both European and American cultivars as well as advanced selections from various breeding programmes. A total of 298 full-sib families were realized, including 26 reciprocal families. No reciprocal differences were found. On a plot-mean basis, the broad-sense heritability was found to be intermediate, H(2) = 0.44-0.50, depending on whether the pedigree information was included in the model or not. The increase was mainly due to a substantial increase in the additive variance component. Likewise, the narrow-sense heritability increased from h(2) = 0.39 to h(2) = 0.45 when the pedigree information was included, while the ratio of the specific combining ability variance to the general combining ability variance fell from 13% to 10%. The predicted breeding values of the 63 parents demonstrate that important cultivars such as Elsanta and Korona are unlikely to produce progenies with a high degree of resistance. On the other hand, the Norwegian cultivar Solprins, the Canadian cultivar Kent and the Italian cultivar Patty appeared to give highly resistant progeny. At the full-sib level, the estimated disease scores ranged from 1.15 (Kent x Induka) to 4.19 (Cavendish x Avanta), revealing a huge range of variation for powdery mildew resistance available for selection.

  12. Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in terms of Phenotypic Variances

    OpenAIRE

    Kaneko, Kunihiko

    2013-01-01

    The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The r...

  13. Analysis of variance: Comfortless questions

    OpenAIRE

    L.V. Nedorezov

    2017-01-01

    In this paper the simplest variant of analysis of variance is under consideration. Three examples from textbooks by Lakin (1990) and Rokitsky (1973) were re-considered. It was obtained that traditional one-way ANOVA and Kruskal - Wallis criterion can lead to unreal results about factor's influence on value of characteristics. Alternative way to solution of the same problem is under consideration too.

  14. Analysis of Variance: Variably Complex

    Science.gov (United States)

    Drummond, Gordon B.; Vowler, Sarah L.

    2012-01-01

    These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution of…

  15. Heritable Micro-environmental Variance Covaries with Fitness in an Outbred Population of Drosophila serrata.

    Science.gov (United States)

    Sztepanacz, Jacqueline L; McGuigan, Katrina; Blows, Mark W

    2017-08-01

    The genetic basis of stochastic variation within a defined environment, and the consequences of such micro-environmental variance for fitness are poorly understood . Using a multigenerational breeding design in Drosophila serrata, we demonstrated that the micro-environmental variance in a set of morphological wing traits in a randomly mating population had significant additive genetic variance in most single wing traits. Although heritability was generally low (micro-environmental variance is an evolvable trait. Multivariate analyses demonstrated that the micro-environmental variance in wings was genetically correlated among single traits, indicating that common mechanisms of environmental buffering exist for this functionally related set of traits. In addition, through the dominance genetic covariance between the major axes of micro-environmental variance and fitness, we demonstrated that micro-environmental variance shares a genetic basis with fitness, and that the pattern of selection is suggestive of variance-reducing selection acting on micro-environmental variance. Copyright © 2017 by the Genetics Society of America.

  16. Functional analysis of variance for association studies.

    Directory of Open Access Journals (Sweden)

    Olga A Vsevolozhskaya

    Full Text Available While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1 it tests for a joint effect of gene variants, including both common and rare; (2 it fully utilizes linkage disequilibrium and genetic position information; and (3 allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods - SKAT and a previously proposed method based on functional linear models (FLM, - especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.

  17. 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.

  18. Variance decomposition in stochastic simulators

    KAUST Repository

    Le Maître, O. P.

    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.

  19. 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.

  20. 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.

  1. Estimativas de variância genética aditiva em populações selecionadas e não-selecionadas via simulação Monte Carlo utilizando o software R Additive genetic variance estimates in selected and unselected populations via Monte Carlo simulation using the R software

    Directory of Open Access Journals (Sweden)

    Ricardo Luis dos Reis

    2009-02-01

    Full Text Available Para disponibilizar um sistema de fornecimento de dados que objetivando-se subsidiar pesquisas de Melhoramento Genético Animal direcionadas à comparação de metodologias de avaliação genética, foi avaliado o comportamento da variância genética aditiva de populações selecionadas e não selecionadas, por seis gerações sucessivas, via simulação Monte Carlo. Por meio de um modelo genético aditivo, foram simuladas populações de 40 animais (20 machos e 20 fêmeas, sob seleção e acasalamento aleatório. Da geração zero até a quinta geração notou-se na população selecionada uma redução de 44,4% na variância genética aditiva, devido a um aumento de 11,58% no coeficiente de endogamia. Na população não selecionada a redução da variância genética aditiva foi menor (27,46% em relação à população selecionada, também devido a aumento de 10,26% no coeficiente de endogamia.The additive genetic variance in selected and unselected populations was evaluated in six successive generations via Monte Carlo simulation. The aim was to build a data system to help researches compare genetic evaluation methodologies in Animal Breeding. By means of an additive genetic model, populations of 40 individuals (20 males and 20 females were simulated, under selected and random mating system. From the generation zero until the fifth generation, the selected population showed reduction of 44.4% in additive genetic variance due to an increase of 11.58% in inbreeding coefficient. In the unselected population the reduction in additive genetic variance was lower (27.46% in relation to the selected population, due to the increasing of 10.26% in inbreeding coefficient.

  2. µ-Calpain, calpastatin, and growth hormone receptor genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in Angus cattle selected to increase minor haplotype ... frequencies

    Science.gov (United States)

    Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size an...

  3. Variance-based uncertainty relations

    CERN Document Server

    Huang, Yichen

    2010-01-01

    It is hard to overestimate the fundamental importance of uncertainty relations in quantum mechanics. In this work, I propose state-independent variance-based uncertainty relations for arbitrary observables in both finite and infinite dimensional spaces. We recover the Heisenberg uncertainty principle as a special case. By studying examples, we find that the lower bounds provided by our new uncertainty relations are optimal or near-optimal. I illustrate the uses of our new uncertainty relations by showing that they eliminate one common obstacle in a sequence of well-known works in entanglement detection, and thus make these works much easier to access in applications.

  4. The evolution and consequences of sex-specific reproductive variance.

    Science.gov (United States)

    Mullon, Charles; Reuter, Max; Lehmann, Laurent

    2014-01-01

    Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

  5. Neutrino mass without cosmic variance

    CERN Document Server

    LoVerde, Marilena

    2016-01-01

    Measuring the absolute scale of the neutrino masses is one of the most exciting opportunities available with near-term cosmological datasets. Two quantities that are sensitive to neutrino mass, scale-dependent halo bias $b(k)$ and the linear growth parameter $f(k)$ inferred from redshift-space distortions, can be measured without cosmic variance. Unlike the amplitude of the matter power spectrum, which always has a finite error, the error on $b(k)$ and $f(k)$ continues to decrease as the number density of tracers increases. This paper presents forecasts for statistics of galaxy and lensing fields that are sensitive to neutrino mass via $b(k)$ and $f(k)$. The constraints on neutrino mass from the auto- and cross-power spectra of spectroscopic and photometric galaxy samples are weakened by scale-dependent bias unless a very high density of tracers is available. In the high density limit, using multiple tracers allows cosmic-variance to be beaten and the forecasted errors on neutrino mass shrink dramatically. In...

  6. Heritable environmental variance causes nonlinear relationships between traits: application to birth weight and stillbirth of pigs.

    Science.gov (United States)

    Mulder, Herman A; Hill, William G; Knol, Egbert F

    2015-04-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others. Copyright © 2015 by the Genetics Society of America.

  7. Warped functional analysis of variance.

    Science.gov (United States)

    Gervini, Daniel; Carter, Patrick A

    2014-09-01

    This article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time-warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability. The focus is on single-random-factor models but the approach can be easily generalized to more complex ANOVA models. The behavior of the estimators is studied by simulation, and an application to the analysis of growth curves of flour beetles is presented. Although the model assumes a smooth latent process behind the observed trajectories, smootheness of the observed data is not required; the method can be applied to irregular time grids, which are common in longitudinal studies.

  8. 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.

  9. 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…

  10. Variance optimal stopping for geometric Levy processes

    DEFF Research Database (Denmark)

    Gad, Kamille Sofie Tågholt; Pedersen, Jesper Lund

    2015-01-01

    The main result of this paper is the solution to the optimal stopping problem of maximizing the variance of a geometric Lévy process. We call this problem the variance problem. We show that, for some geometric Lévy processes, we achieve higher variances by allowing randomized stopping. Furthermore...

  11. Heterogeneity of variances for carcass traits by percentage Brahman inheritance.

    Science.gov (United States)

    Crews, D H; Franke, D E

    1998-07-01

    Heterogeneity of carcass trait variances due to level of Brahman inheritance was investigated using records from straightbred and crossbred steers produced from 1970 to 1988 (n = 1,530). Angus, Brahman, Charolais, and Hereford sires were mated to straightbred and crossbred cows to produce straightbred, F1, back-cross, three-breed cross, and two-, three-, and four-breed rotational crossbred steers in four non-overlapping generations. At weaning (mean age = 220 d), steers were randomly assigned within breed group directly to the feedlot for 200 d, or to a backgrounding and stocker phase before feeding. Stocker steers were fed from 70 to 100 d in generations 1 and 2 and from 60 to 120 d in generations 3 and 4. Carcass traits included hot carcass weight, subcutaneous fat thickness and longissimus muscle area at the 12-13th rib interface, carcass weight-adjusted longissimus muscle area, USDA yield grade, estimated total lean yield, marbling score, and Warner-Bratzler shear force. Steers were classified as either high Brahman (50 to 100% Brahman), moderate Brahman (25 to 49% Brahman), or low Brahman (0 to 24% Brahman) inheritance. Two types of animal models were fit with regard to level of Brahman inheritance. One model assumed similar variances between pairs of Brahman inheritance groups, and the second model assumed different variances between pairs of Brahman inheritance groups. Fixed sources of variation in both models included direct and maternal additive and nonadditive breed effects, year of birth, and slaughter age. Variances were estimated using derivative free REML procedures. Likelihood ratio tests were used to compare models. The model accounting for heterogeneous variances had a greater likelihood (P carcass weight, longissimus muscle area, weight-adjusted longissimus muscle area, total lean yield, and Warner-Bratzler shear force, indicating improved fit with percentage Brahman inheritance considered as a source of heterogeneity of variance. Genetic

  12. Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

    NARCIS (Netherlands)

    Mulder, H.A.; Hill, W.G.; Knol, E.F.

    2015-01-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of oth

  13. Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

    NARCIS (Netherlands)

    Mulder, H.A.; Hill, W.G.; Knol, E.F.

    2015-01-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of

  14. Linear Minimum variance estimation fusion

    Institute of Scientific and Technical Information of China (English)

    ZHU Yunmin; LI Xianrong; ZHAO Juan

    2004-01-01

    This paper shows that a general mulitisensor unbiased linearly weighted estimation fusion essentially is the linear minimum variance (LMV) estimation with linear equality constraint, and the general estimation fusion formula is developed by extending the Gauss-Markov estimation to the random paramem of distributed estimation fusion in the LMV setting.In this setting ,the fused estimator is a weighted sum of local estimatess with a matrix quadratic optimization problem subject to a convex linear equality constraint. Second, we present a unique solution to the above optimization problem, which depends only on the covariance matrixCK. Third, if a priori information, the expectation and covariance, of the estimated quantity is unknown, a necessary and sufficient condition for the above LMV fusion becoming the best unbiased LMV estimation with dnown prior information as the above is presented. We also discuss the generality and usefulness of the LMV fusion formulas developed. Finally, we provied and off-line recursion of Ck for a class of multisensor linear systems with coupled measurement noises.

  15. Genetic Variance in Uncoupling Protein 2 in Relation to Obesity, Type 2 Diabetes, and Related Metabolic Traits: Focus on the Functional −866G>A Promoter Variant (rs659366

    Directory of Open Access Journals (Sweden)

    Louise T. Dalgaard

    2011-01-01

    Full Text Available Uncoupling proteins (UCPs are mitochondrial proteins able to dissipate the proton gradient of the inner mitochondrial membrane when activated. This decreases ATP-generation through oxidation of fuels and may theoretically decrease energy expenditure leading to obesity. Evidence from Ucp(−/− mice revealed a role of UCP2 in the pancreatic β-cell, because β-cells without UCP2 had increased glucose-stimulated insulin secretion. Thus, from being a candidate gene for obesity UCP2 became a valid candidate gene for type 2 diabetes mellitus. This prompted a series of studies of the human UCP2 and UCP3 genes with respect to obesity and diabetes. Of special interest was a promoter variant of UCP2 situated 866bp upstream of transcription initiation (−866G>A, rs659366. This variant changes promoter activity and has been associated with obesity and/or type 2 diabetes in several, although not all, studies. The aim of the current paper is to summarize current evidence of association of UCP2 genetic variation with obesity and type 2 diabetes, with focus on the −866G>A polymorphism.

  16. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  17. Estimation of the additive and dominance variances in South African Landrace pigs

    OpenAIRE

    Norris, D.; Varona Aguado, Luís; Visser, D. P.; Theron, H. E.; Voordewind, S. F.; Nesambuni, E. A.

    2006-01-01

    The objective of this study was to estimate dominance variance for number born alive (NBA), 21- day litter weight (LWT21) and interval between parities (FI) in South African Landrace pigs. A total of 26223 NBA, 21335 LWT21 and 16370 FI records were analysed. Bayesian analysis via Gibbs sampling was used to estimate variance components and genetic parameters were calculated from posterior distributions. Estimates of additive genetic variance were 0.669, 43.46 d2 and 9.02 kg2 for NBA, FI and LW...

  18. Componentes de (covariância e parâmetros genéticos de características de crescimento da raça Simental no Brasil Variance components and genetic parameters estimates for growth traits of Simmental cattle in Brazil

    Directory of Open Access Journals (Sweden)

    L.F.A. Marques

    1999-08-01

    Full Text Available Informações de genealogia e produção, cedidas pela Associação Brasileira de Criadores da Raça Simental (ABCRS, relativas aos pesos desde o nascimento até um ano de idade, foram utilizadas para estimar, sob modelos alternativos, os componentes de variância e os parâmetros genéticos em animais da raça Simental no Brasil. A matriz de parentesco incluiu 25.812 animais dos quais 7587 com dados de produção. O modelo 1 contém, além do erro, o efeito genético direto. Os modelos seguintes contêm os componentes do modelo 1, mais o efeito permanente de ambiente materno (modelo 2, ou o componente genético materno (modelo 3, ambos os componentes (modelo 5, os componentes do modelo 3 mais a covariância entre os efeitos genéticos direto e materno (modelo 4 e todos os componentes citados (modelo 6. Os modelos foram comparados pelo teste de razão de verossimilhança pelo chi² (PBirth, 100-day, weaning and yearling weights of 7587 Simmental cattle, and 25,812 pedigree data were used to estimate genetic parameters using different animal models. The simplest model (model l included additive genetic and residual random effects. Models 2 and 3 were the same as model 1, but included, respectively, maternal permanent and maternal genetic effects. Model 4 did not include permanent effect. The most complete model (model 6 also included maternal additive and permanent effects, assuming covariance between them. Model 5 was the same as model 6, but did not included direct maternal covariance. Contemporary groups considered animals born in the same herd, year and season, from the same sex and raised under the same nutritional system. The models were compared using likelihood ratio tests. The (covariance components and the genetic parameters decreased from the most simple (model 1 to the most complete model (model 6. One-hundred-day weight showed no (.00±.00 maternal genetic variance but moderate maternal environmental permanent effect (.17±.07. The

  19. The phenotypic variance gradient - a novel concept.

    Science.gov (United States)

    Pertoldi, Cino; Bundgaard, Jørgen; Loeschcke, Volker; Barker, James Stuart Flinton

    2014-11-01

    Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life-history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely "a plot of log (variance) on the y-axis versus log (mean) on the x-axis, with a reference line added". This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a "phenotypic variance gradient", are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.

  20. Expected Stock Returns and Variance Risk Premia

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Zhou, Hao

    predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance...... 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...

  1. Within-generation mutation variance for litter size in inbred mice.

    Science.gov (United States)

    Casellas, Joaquim; Medrano, Juan F

    2008-08-01

    The mutational input of genetic variance per generation (sigma(m)(2)) is the lower limit of the genetic variability in inbred strains of mice, although greater values could be expected due to the accumulation of new mutations in successive generations. A mixed-model analysis using Bayesian methods was applied to estimate sigma(m)(2) and the across-generation accumulated genetic variability on litter size in 46 generations of a C57BL/6J inbred strain. This allowed for a separate inference on sigma(m)(2) and on the additive genetic variance in the base population (sigma(a)(2)). The additive genetic variance in the base generation was 0.151 and quickly decreased to almost null estimates in generation 10. On the other hand, sigma(m)(2) was moderate (0.035) and the within-generation mutational variance increased up to generation 14, then oscillating between 0.102 and 0.234 in remaining generations. This pattern suggested the existence of a continuous uploading of genetic variability for litter size (h(2)=0.045). Relevant genetic drift was not detected in this population. In conclusion, our approach allowed for separate estimation of sigma(a)(2) and sigma(m)(2) within the mixed-model framework, and the heritability obtained highlighted the significant and continuous influence of new genetic variability affecting the genetic stability of inbred strains.

  2. 21 CFR 1010.4 - Variances.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Variances. 1010.4 Section 1010.4 Food and Drugs... PERFORMANCE STANDARDS FOR ELECTRONIC PRODUCTS: GENERAL General Provisions § 1010.4 Variances. (a) Criteria for... shall modify the tag, label, or other certification required by § 1010.2 to state: (1) That the...

  3. Analysis of variance for model output

    NARCIS (Netherlands)

    Jansen, M.J.W.

    1999-01-01

    A scalar model output Y is assumed to depend deterministically on a set of stochastically independent input vectors of different dimensions. The composition of the variance of Y is considered; variance components of particular relevance for uncertainty analysis are identified. Several analysis of va

  4. The Correct Kriging Variance Estimated by Bootstrapping

    NARCIS (Netherlands)

    den Hertog, D.; Kleijnen, J.P.C.; Siem, A.Y.D.

    2004-01-01

    The classic Kriging variance formula is widely used in geostatistics and in the design and analysis of computer experiments.This paper proves that this formula is wrong.Furthermore, it shows that the formula underestimates the Kriging variance in expectation.The paper develops parametric bootstrappi

  5. Variance Risk Premia on Stocks and Bonds

    DEFF Research Database (Denmark)

    Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea

    is different from the equity variance risk premium. Third, the conditional correlation between stock and bond market variance risk premium switches sign often and ranges between -60% and +90%. We then show that these stylized facts pose a challenge to standard consumption-based asset pricing models....

  6. Influência da heterogeneidade de variâncias na avaliação genética de bovinos de corte da raça Tabapuã Influence of heterogeneity of variances on genetic evaluation of Tabapuã beef cattle

    Directory of Open Access Journals (Sweden)

    J.E.G. Campelo

    2003-12-01

    Full Text Available Verificou-se a influência da heterogeneidade de variâncias na avaliação genética de bovinos de corte da raça Tabapuã. Dados de pesos corrigidos aos 120, 240 e 420 dias de idade foram estratificados com base no desvio-padrão fenotípico do peso aos 120 dias dos grupos de contemporâneos em três classes: baixo (18,9kg desvio-padrão. Nas análises de múltiplas características, em que o peso foi considerado característica distinta em cada classe de desvio-padrão, constatou-se que as variâncias genéticas e residuais foram maiores com o aumento do desvio-padrão da classe. As herdabilidades foram 0,26, 0,32 e 0,37 (peso aos 120 dias, 0,28, 0,35 e 0,35 (peso aos 240 dias e 0,14, 0,18 e 0,18 (peso aos 420 dias nas classes de baixo, médio e alto desvio-padrão, respectivamente. As correlações genéticas entre o mesmo peso, nas classes de baixo e alto desvio-padrão foram inferiores a 0,80. As correlações entre os valores genéticos, obtidos de análises múltiplas e de análise geral (sem as classes, foram superiores a 0,93. Observou-se que os reprodutores seriam classificados de forma similar se for considerada ou não a presença de variâncias heterogêneas nas análises.Data from Tabapuã beef cattle were used to study the influence of variance heterogeneity on genetic evaluation. Adjusted weights at 120, 240 and 420 days of age were classified in three classes of standard deviation: low (18.9kg, based on phenotypic standard deviation of the weight at 120 days of age of the contemporary groups. Multiple trait analyses, considering each class of phenotypic standard deviation as a distinct trait, were performed. The genetic and residual variances increased as the phenotypic standard deviation of the class increased. Heritabilities for low, medium and high phenotypic standard deviation classes were 0.26, 0.32 and 0.37 (weight at 120 days, 0.28, 0.35 and 0.35 (weight at 240 days and 0.14, 0.18 and 0.18 (weight at 420 days

  7. Genetic parameters and heterogeneity of variance to milk yield in Murrah breed for Bayesian inference Heterogeneidade de variâncias e parâmetros genéticos para produção de leite em bubalinos da raça Murrah, mediante inferência Bayesiana

    Directory of Open Access Journals (Sweden)

    Simone Inoe Araújo

    2008-09-01

    Full Text Available Data from 2061 lactations of 532 females of the Murrah breed, daughters of 44 sires, calving from 1975 to 2001 were used to evaluate the effects of heterogeneity at variance on sires genetic evaluation. The standard deviation of the milk yield was used to classify the herds among high and low variability levels. An animal model, used to estimate variance component, included the fixed effect of herds-year, season of calving, animal random effect, permanent and temporary environments. Variance components were estimated to milk yield in both levels, considering the milk yield in each production level as different trait. Estimatives of heritability were 0.39, in general analysis, and equal to 0.33 and 0.41 for milk yield in high and low levels, respectively. Genetic correlations between high and low production levels were 58. The sires were selected according to the environment most changeable where daughters are raised, and not properly for its genetic breeding.Informações de 2061 registros de lactações de 532 fêmeas da raça Murrah, filhas de 44 reprodutores, com parições entre 1975 a 2001, foram utilizadas para se verificar a existência da heterogeneidade de variância para a produção de leite entre rebanhos e o seu impacto na classificação de reprodutores. O desvio padrão da produção de leite entre rebanhos foi utilizado para classificação dos rebanhos em níveis de alta e baixa variabilidade. Utilizou-se um modelo animal que incluiu os efeitos fixos de rebanho-ano, estação de parição, efeitos aleatórios de animal, ambiente permanente e ambiente temporário. Foram estimados os componentes de variância, considerando os rebanhos como uma única amostra e assumindo a produção de leite em cada nível de produção como característica diferente. Médias e componentes de variância foram maiores para o nível de alta produção e as estimativas de herdabilidade foram de 0,39 em ambos os níveis para a produção de leite e 0

  8. Portfolio optimization with mean-variance model

    Science.gov (United States)

    Hoe, Lam Weng; Siew, Lam Weng

    2016-06-01

    Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

  9. Expected Stock Returns and Variance Risk Premia

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Zhou, Hao

    We find that the difference between implied and realized variation, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia...... predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance...... 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...

  10. Estimation of Epistatic Variance Components and Heritability in Founder Populations and Crosses

    Science.gov (United States)

    Young, Alexander I.; Durbin, Richard

    2014-01-01

    Genetic association studies have explained only a small proportion of the estimated heritability of complex traits, leaving the remaining heritability “missing.” Genetic interactions have been proposed as an explanation for this, because they lead to overestimates of the heritability and are hard to detect. Whether this explanation is true depends on the proportion of variance attributable to genetic interactions, which is difficult to measure in outbred populations. Founder populations exhibit a greater range of kinship than outbred populations, which helps in fitting the epistatic variance. We extend classic theory to founder populations, giving the covariance between individuals due to epistasis of any order. We recover the classic theory as a limit, and we derive a recently proposed estimator of the narrow sense heritability as a corollary. We extend the variance decomposition to include dominance. We show in simulations that it would be possible to estimate the variance from pairwise interactions with samples of a few thousand from strongly bottlenecked human founder populations, and we provide an analytical approximation of the standard error. Applying these methods to 46 traits measured in a yeast (Saccharomyces cerevisiae) cross, we estimate that pairwise interactions explain 10% of the phenotypic variance on average and that third- and higher-order interactions explain 14% of the phenotypic variance on average. We search for third-order interactions, discovering an interaction that is shared between two traits. Our methods will be relevant to future studies of epistatic variance in founder populations and crosses. PMID:25326236

  11. Components of the metabolic syndrome: clustering and genetic variance

    NARCIS (Netherlands)

    Povel, C.M.

    2012-01-01

    Background Abdominal obesity, hyperglycemia, hypertriglyceridemia, low HDL cholesterol levels and hypertension frequently co-occur within individuals. The cluster of these features is referred to as the metabolic syndrome (MetS). The aim

  12. On the additive and dominant variance and covariance of individuals within the genomic selection scope.

    Science.gov (United States)

    Vitezica, Zulma G; Varona, Luis; Legarra, Andres

    2013-12-01

    Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or "breeding" values of individuals are generated by substitution effects, which involve both "biological" additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the "genotypic" value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.

  13. Portfolio optimization using median-variance approach

    Science.gov (United States)

    Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

    2013-04-01

    Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

  14. Reducing variance in batch partitioning measurements

    Energy Technology Data Exchange (ETDEWEB)

    Mariner, Paul E.

    2010-08-11

    The partitioning experiment is commonly performed with little or no attention to reducing measurement variance. Batch test procedures such as those used to measure K{sub d} values (e.g., ASTM D 4646 and EPA402 -R-99-004A) do not explain how to evaluate measurement uncertainty nor how to minimize measurement variance. In fact, ASTM D 4646 prescribes a sorbent:water ratio that prevents variance minimization. Consequently, the variance of a set of partitioning measurements can be extreme and even absurd. Such data sets, which are commonplace, hamper probabilistic modeling efforts. An error-savvy design requires adjustment of the solution:sorbent ratio so that approximately half of the sorbate partitions to the sorbent. Results of Monte Carlo simulations indicate that this simple step can markedly improve the precision and statistical characterization of partitioning uncertainty.

  15. 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.

  16. 78 FR 14122 - Revocation of Permanent Variances

    Science.gov (United States)

    2013-03-04

    ... Occupational Safety and Health Administration Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA), Labor. ACTION: Notice of revocation. SUMMARY: With this notice, OSHA is... into consideration these newly corrected cross references. DATES: The effective date of the...

  17. Importance Sampling Variance Reduction in GRESS ATMOSIM

    Energy Technology Data Exchange (ETDEWEB)

    Wakeford, Daniel Tyler [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-04-26

    This document is intended to introduce the importance sampling method of variance reduction to a Geant4 user for application to neutral particle Monte Carlo transport through the atmosphere, as implemented in GRESS ATMOSIM.

  18. 13 CFR 307.22 - Variances.

    Science.gov (United States)

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Variances. 307.22 Section 307.22 Business Credit and Assistance ECONOMIC DEVELOPMENT ADMINISTRATION, DEPARTMENT OF COMMERCE ECONOMIC... Federal, State and local law....

  19. Variance components in discrete force production tasks.

    Science.gov (United States)

    Varadhan, S K M; Zatsiorsky, Vladimir M; Latash, Mark L

    2010-09-01

    The study addresses the relationships between task parameters and two components of variance, "good" and "bad", during multi-finger accurate force production. The variance components are defined in the space of commands to the fingers (finger modes) and refer to variance that does ("bad") and does not ("good") affect total force. Based on an earlier study of cyclic force production, we hypothesized that speeding-up an accurate force production task would be accompanied by a drop in the regression coefficient linking the "bad" variance and force rate such that variance of the total force remains largely unaffected. We also explored changes in parameters of anticipatory synergy adjustments with speeding-up the task. The subjects produced accurate ramps of total force over different times and in different directions (force-up and force-down) while pressing with the four fingers of the right hand on individual force sensors. The two variance components were quantified, and their normalized difference was used as an index of a total force stabilizing synergy. "Good" variance scaled linearly with force magnitude and did not depend on force rate. "Bad" variance scaled linearly with force rate within each task, and the scaling coefficient did not change across tasks with different ramp times. As a result, a drop in force ramp time was associated with an increase in total force variance, unlike the results of the study of cyclic tasks. The synergy index dropped 100-200 ms prior to the first visible signs of force change. The timing and magnitude of these anticipatory synergy adjustments did not depend on the ramp time. Analysis of the data within an earlier model has shown adjustments in the variance of a timing parameter, although these adjustments were not as pronounced as in the earlier study of cyclic force production. Overall, we observed qualitative differences between the discrete and cyclic force production tasks: Speeding-up the cyclic tasks was associated with

  20. Discrimination of frequency variance for tonal sequencesa)

    OpenAIRE

    Byrne, Andrew J.; Viemeister, Neal F.; Stellmack, Mark A.

    2014-01-01

    Real-world auditory stimuli are highly variable across occurrences and sources. The present study examined the sensitivity of human listeners to differences in global stimulus variability. In a two-interval, forced-choice task, variance discrimination was measured using sequences of five 100-ms tone pulses. The frequency of each pulse was sampled randomly from a distribution that was Gaussian in logarithmic frequency. In the non-signal interval, the sampled distribution had a variance of σSTA...

  1. 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.

  2. Modelos animais alternativos para estimação de componentes de (covariância e de parâmetros genéticos e fenotípicos do peso ao nascer na raça Nelore Alternative animal models to estimate (co variance components and genetic and phenotypic parameters for birth weight in Nellore cattle

    Directory of Open Access Journals (Sweden)

    Márcia Tereza Vieira Scarpati

    1999-01-01

    artificial insemination were considered. The (co variance components were estimated under four different animal models where direct and maternal genetic and permanent environmental were taken into account by including the appropriate random effects, as well as contemporary groups and age of cow at calving effects, in the statistical model. This procedure allowed the quantification of the contribution of different random effects, especially maternal effects. The number of records was 6511; the overall means 31 kg, and the standard deviation 4,1 kg. The direct, maternal and total estimated heritability ranged from 0.20 to 0.37, 0.11 to 0.13 and 0.22 to 0.37, respectively. The correlation's between genetic direct and maternal effects were negative (-0,14 to ¾0,16. The BW is a trait greatly determined by direct additive genic action, insignificantly affected by maternal phenotype, and with antagonism between the genetic effects. Response to selection for BW would be maximized if based on the parameters obtained by the analysis fitting animal models with direct and maternal effects.

  3. Variance component estimates for alternative litter size traits in swine.

    Science.gov (United States)

    Putz, A M; Tiezzi, F; Maltecca, C; Gray, K A; Knauer, M T

    2015-11-01

    Litter size at d 5 (LS5) has been shown to be an effective trait to increase total number born (TNB) while simultaneously decreasing preweaning mortality. The objective of this study was to determine the optimal litter size day for selection (i.e., other than d 5). Traits included TNB, number born alive (NBA), litter size at d 2, 5, 10, 30 (LS2, LS5, LS10, LS30, respectively), litter size at weaning (LSW), number weaned (NW), piglet mortality at d 30 (MortD30), and average piglet birth weight (BirthWt). Litter size traits were assigned to biological litters and treated as a trait of the sow. In contrast, NW was the number of piglets weaned by the nurse dam. Bivariate animal models included farm, year-season, and parity as fixed effects. Number born alive was fit as a covariate for BirthWt. Random effects included additive genetics and the permanent environment of the sow. Variance components were plotted for TNB, NBA, and LS2 to LS30 using univariate animal models to determine how variances changed over time. Additive genetic variance was minimized at d 7 in Large White and at d 14 in Landrace pigs. Total phenotypic variance for litter size traits decreased over the first 10 d and then stabilized. Heritability estimates increased between TNB and LS30. Genetic correlations between TNB, NBA, and LS2 to LS29 with LS30 plateaued within the first 10 d. A genetic correlation with LS30 of 0.95 was reached at d 4 for Large White and at d 8 for Landrace pigs. Heritability estimates ranged from 0.07 to 0.13 for litter size traits and MortD30. Birth weight had an h of 0.24 and 0.26 for Large White and Landrace pigs, respectively. Genetic correlations among LS30, LSW, and NW ranged from 0.97 to 1.00. In the Large White breed, genetic correlations between MortD30 with TNB and LS30 were 0.23 and -0.64, respectively. These correlations were 0.10 and -0.61 in the Landrace breed. A high genetic correlation of 0.98 and 0.97 was observed between LS10 and NW for Large White and

  4. Discrimination of frequency variance for tonal sequences.

    Science.gov (United States)

    Byrne, Andrew J; Viemeister, Neal F; Stellmack, Mark A

    2014-12-01

    Real-world auditory stimuli are highly variable across occurrences and sources. The present study examined the sensitivity of human listeners to differences in global stimulus variability. In a two-interval, forced-choice task, variance discrimination was measured using sequences of five 100-ms tone pulses. The frequency of each pulse was sampled randomly from a distribution that was Gaussian in logarithmic frequency. In the non-signal interval, the sampled distribution had a variance of σSTAN (2), while in the signal interval, the variance of the sequence was σSIG (2) (with σSIG (2) >  σSTAN (2)). The listener's task was to choose the interval with the larger variance. To constrain possible decision strategies, the mean frequency of the sampling distribution of each interval was randomly chosen for each presentation. Psychometric functions were measured for various values of σSTAN (2). Although the performance was remarkably similar across listeners, overall performance was poorer than that of an ideal observer (IO) which perfectly compares interval variances. However, like the IO, Weber's Law behavior was observed, with a constant ratio of ( σSIG (2)- σSTAN (2)) to σSTAN (2) yielding similar performance. A model which degraded the IO with a frequency-resolution noise and a computational noise provided a reasonable fit to the real data.

  5. Maximum Variance Hashing via Column Generation

    Directory of Open Access Journals (Sweden)

    Lei Luo

    2013-01-01

    item search. Recently, a number of data-dependent methods have been developed, reflecting the great potential of learning for hashing. Inspired by the classic nonlinear dimensionality reduction algorithm—maximum variance unfolding, we propose a novel unsupervised hashing method, named maximum variance hashing, in this work. The idea is to maximize the total variance of the hash codes while preserving the local structure of the training data. To solve the derived optimization problem, we propose a column generation algorithm, which directly learns the binary-valued hash functions. We then extend it using anchor graphs to reduce the computational cost. Experiments on large-scale image datasets demonstrate that the proposed method outperforms state-of-the-art hashing methods in many cases.

  6. Estimating quadratic variation using realized variance

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Shephard, N.

    2002-01-01

    This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process is a semimar......This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process...... 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....

  7. 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.

  8. A Mean-Variance Hybrid-Entropy Model for Portfolio Selection with Fuzzy Returns

    Directory of Open Access Journals (Sweden)

    Rongxi Zhou

    2015-05-01

    Full Text Available In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM. A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II is introduced to solve the model. We make empirical comparisons by using the data from the Shanghai and Shenzhen stock exchanges in China. The results show that the MVHEM generally performs better than the traditional portfolio selection models.

  9. Sources of variance in ocular microtremor.

    Science.gov (United States)

    Sheahan, N F; Coakley, D; Bolger, C; O'Neill, D; Fry, G; Phillips, J; Malone, J F

    1994-02-01

    This study presents a preliminary investigation of the sources of variance in the measurement of ocular microtremor frequency in a normal population. When the results from both experienced and relatively inexperienced operators are pooled, factors that contribute significantly to the total variance include the measurement procedure (p < 0.001), day-to-day variations within subjects (p < 0.001), and inter-subject differences (p < 0.01). Operator experience plays a role in determining the measurement precision: the intra-subject coefficient of variation is about 5% for a very experienced operator, and about 14% for a relatively inexperienced operator.

  10. Managing product inherent variance during treatment

    NARCIS (Netherlands)

    Verdenius, F.

    1996-01-01

    The natural variance of agricultural product parameters complicates recipe planning for product treatment, i.e. the process of transforming a product batch from its initial state to a prespecified final state. For a specific product P, recipes are currently composed by human experts on the basis of

  11. The Variance of Language in Different Contexts

    Institute of Scientific and Technical Information of China (English)

    申一宁

    2012-01-01

    language can be quite different (here referring to the meaning) in different contexts. And there are 3 categories of context: the culture, the situation and the cotext. In this article, we will analysis the variance of language in each of the 3 aspects. This article is written for the purpose of making people understand the meaning of a language under specific better.

  12. Regression calibration with heteroscedastic error variance.

    Science.gov (United States)

    Spiegelman, Donna; Logan, Roger; Grove, Douglas

    2011-01-01

    The problem of covariate measurement error with heteroscedastic measurement error variance is considered. Standard regression calibration assumes that the measurement error has a homoscedastic measurement error variance. An estimator is proposed to correct regression coefficients for covariate measurement error with heteroscedastic variance. Point and interval estimates are derived. Validation data containing the gold standard must be available. This estimator is a closed-form correction of the uncorrected primary regression coefficients, which may be of logistic or Cox proportional hazards model form, and is closely related to the version of regression calibration developed by Rosner et al. (1990). The primary regression model can include multiple covariates measured without error. The use of these estimators is illustrated in two data sets, one taken from occupational epidemiology (the ACE study) and one taken from nutritional epidemiology (the Nurses' Health Study). In both cases, although there was evidence of moderate heteroscedasticity, there was little difference in estimation or inference using this new procedure compared to standard regression calibration. It is shown theoretically that unless the relative risk is large or measurement error severe, standard regression calibration approximations will typically be adequate, even with moderate heteroscedasticity in the measurement error model variance. In a detailed simulation study, standard regression calibration performed either as well as or better than the new estimator. When the disease is rare and the errors normally distributed, or when measurement error is moderate, standard regression calibration remains the method of choice.

  13. 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 intr

  14. Formative Use of Intuitive Analysis of Variance

    Science.gov (United States)

    Trumpower, David L.

    2013-01-01

    Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In…

  15. Linear transformations of variance/covariance matrices

    NARCIS (Netherlands)

    Parois, P.J.A.; Lutz, M.

    2011-01-01

    Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance

  16. 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 intr

  17. 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...

  18. 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...

  19. 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...

  20. 40 CFR 142.43 - Disposition of a variance request.

    Science.gov (United States)

    2010-07-01

    ... during the period of variance shall specify interim treatment techniques, methods and equipment, and... the specified treatment technique for which the variance was granted is necessary to protect...

  1. Variance estimation between different body measurements at the males population from Romanian Mioritic Shepherd Dog breed

    Directory of Open Access Journals (Sweden)

    Dorel Dronca

    2015-05-01

    Full Text Available Romanian Mioritic Shepherd Dog, was selected from a natural population breed in Carpathian Mountains. The aim of this paper was to estimate variance at 12 body measurements using 26 males from Romanian Mioritic Shepherd Dog breed. The animals were registered with the Romanian Mioritic Association Club from Romania. The statistical data showed that there is a large variance for body length and tail length, a middle variance for the croup width and thorax width and a small variance for height at withers, height at middle of back, height at croup, height at the base of the tail, depth of thorax, thoracic perimeter, elbow height and height of the hock. We recommend of breeders dogs from this breed to take account in genetic improvement programs, of values presented in this paper.

  2. Estimation models of variance components for farrowing interval in swine

    Directory of Open Access Journals (Sweden)

    Aderbal Cavalcante Neto

    2009-02-01

    Full Text Available The main objective of this study was to evaluate the importance of including maternal genetic, common litter environmental and permanent environmental effects in estimation models of variance components for the farrowing interval trait in swine. Data consisting of 1,013 farrowing intervals of Dalland (C-40 sows recorded in two herds were analyzed. Variance components were obtained by the derivative-free restricted maximum likelihood method. Eight models were tested which contained the fixed effects(contemporary group and covariables and the direct genetic additive and residual effects, and varied regarding the inclusion of the maternal genetic, common litter environmental, and/or permanent environmental random effects. The likelihood-ratio test indicated that the inclusion of these effects in the model was unnecessary, but the inclusion of the permanent environmental effect caused changes in the estimates of heritability, which varied from 0.00 to 0.03. In conclusion, the heritability values obtained indicated that this trait appears to present no genetic gain as response to selection. The common litter environmental and the maternal genetic effects did not present any influence on this trait. The permanent environmental effect, however, should be considered in the genetic models for this trait in swine, because its presence caused changes in the additive genetic variance estimates.Este trabalho teve como objetivo principal avaliar a importância da inclusão dos efeitos genético materno, comum de leitegada e de ambiente permanente no modelo de estimação de componentes de variância para a característica intervalo de parto em fêmeas suínas. Foram utilizados dados que consistiam de 1.013 observações de fêmeas Dalland (C-40, registradas em dois rebanhos. As estimativas dos componentes de variância foram realizadas pelo método da máxima verossimilhança restrita livre de derivadas. Foram testados oito modelos, que continham os efeitos

  3. Partitioning of genomic variance using biological pathways

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon; Janss, Luc; Madsen, Per;

    for complex diseases reveals patterns that provide insight into the genetic architecture of complex traits. Although many genetic variants with small or moderate effects contribute to the overall genetic variation, it appears that multiple independently associated variants are located in the same genes...... diseases. However, the variants identified as being statistically significant have generally explained only a small fraction of the heritable component of the trait. Insufficient modelling of the underlying genetic architecture may in part explain this missing heritability. Evidence collected across GWAS...

  4. 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...

  5. Linear transformations of variance/covariance matrices.

    Science.gov (United States)

    Parois, Pascal; Lutz, Martin

    2011-07-01

    Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance matrix. For the transformation of second-rank tensors it is suggested that the 3 × 3 matrix is re-written into a 9 × 1 vector. The transformation of the corresponding variance/covariance matrix is then straightforward and easily implemented into computer software. This method is applied in the transformation of anisotropic displacement parameters, the calculation of equivalent isotropic displacement parameters, the comparison of refinements in different space-group settings and the calculation of standard uncertainties of eigenvalues.

  6. Variance and covariance of accumulated displacement estimates.

    Science.gov (United States)

    Bayer, Matthew; Hall, Timothy J

    2013-04-01

    Tracking large deformations in tissue using ultrasound can enable the reconstruction of nonlinear elastic parameters, but poses a challenge to displacement estimation algorithms. Such large deformations have to be broken up into steps, each of which contributes an estimation error to the final accumulated displacement map. The work reported here measured the error variance for single-step and accumulated displacement estimates using one-dimensional numerical simulations of ultrasound echo signals, subjected to tissue strain and electronic noise. The covariance between accumulation steps was also computed. These simulations show that errors due to electronic noise are negatively correlated between steps, and therefore accumulate slowly, whereas errors due to tissue deformation are positively correlated and accumulate quickly. For reasonably low electronic noise levels, the error variance in the accumulated displacement estimates is remarkably constant as a function of step size, but increases with the length of the tracking kernel.

  7. 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...

  8. The Theory of Variances in Equilibrium Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren

    2008-01-14

    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.

  9. Eigenvalue variance bounds for covariance matrices

    OpenAIRE

    Dallaporta, Sandrine

    2013-01-01

    This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum. In a preceding paper, the author established analogous results for Wigner matrices and stated the results for covariance matrices. They are proved in the present paper. Relying on the LUE example, which needs to be investigated first, the main bounds are extended to complex covariance matrices by means of the Tao, Vu and Wan...

  10. High-dimensional regression with unknown variance

    CERN Document Server

    Giraud, Christophe; Verzelen, Nicolas

    2011-01-01

    We review recent results for high-dimensional sparse linear regression in the practical case of unknown variance. Different sparsity settings are covered, including coordinate-sparsity, group-sparsity and variation-sparsity. The emphasize is put on non-asymptotic analyses and feasible procedures. In addition, a small numerical study compares the practical performance of three schemes for tuning the Lasso esti- mator and some references are collected for some more general models, including multivariate regression and nonparametric regression.

  11. Fractional constant elasticity of variance model

    OpenAIRE

    Ngai Hang Chan; Chi Tim Ng

    2007-01-01

    This paper develops a European option pricing formula for fractional market models. Although there exist option pricing results for a fractional Black-Scholes model, they are established without accounting for stochastic volatility. In this paper, a fractional version of the Constant Elasticity of Variance (CEV) model is developed. European option pricing formula similar to that of the classical CEV model is obtained and a volatility skew pattern is revealed.

  12. 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.

  13. Variance and covariance components for liability of piglet survival during different periods

    DEFF Research Database (Denmark)

    Su, G; Sorensen, D; Lund, M S

    2008-01-01

    Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual...

  14. 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.)

  15. Applications of non-parametric statistics and analysis of variance on sample variances

    Science.gov (United States)

    Myers, R. H.

    1981-01-01

    Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

  16. The Parabolic variance (PVAR), a wavelet variance based on least-square fit

    CERN Document Server

    Vernotte, F; Bourgeois, P -Y; Rubiola, E

    2015-01-01

    The Allan variance (AVAR) is one option among the wavelet variances. However a milestone in the analysis of frequency fluctuations and in the long-term stability of clocks, and certainly the most widely used one, AVAR is not suitable when fast noise processes show up, chiefly because of the poor rejection of white phase noise. The modified Allan variance (MVAR) features high resolution in the presence of white PM noise, but it is poorer for slow phenomena because the wavelet spans over 50% longer time. This article introduces the Parabolic Variance (PVAR), a wavelet variance similar to the Allan variance, based on the Linear Regression (LR) of phase data. The PVAR relates to the Omega frequency counter, which is the topics of a companion article [the reference to the article, or to the ArXiv manuscript, will be provided later]. The PVAR wavelet spans over 2 tau, the same of the AVAR wavelet. After setting the theoretical framework, we analyze the degrees of freedom and the detection of weak noise processes in...

  17. Double decomposition: decomposing the variance in subcomponents of male extra-pair reproductive success.

    Science.gov (United States)

    Losdat, Sylvain; Arcese, Peter; Reid, Jane M

    2015-09-01

    1. Extra-pair reproductive success (EPRS) is a key component of male fitness in socially monogamous systems and could cause selection on female extra-pair reproduction if extra-pair offspring (EPO) inherit high value for EPRS from their successful extra-pair fathers. However, EPRS is itself a composite trait that can be fully decomposed into subcomponents of variation, each of which can be further decomposed into genetic and environmental variances. However, such decompositions have not been implemented in wild populations, impeding evolutionary inference. 2. We first show that EPRS can be decomposed into the product of three life-history subcomponents: the number of broods available to a focal male to sire EPO, the male's probability of siring an EPO in an available brood and the number of offspring in available broods. This decomposition of EPRS facilitates estimation from field data because all subcomponents can be quantified from paternity data without need to quantify extra-pair matings. Our decomposition also highlights that the number of available broods, and hence population structure and demography, might contribute substantially to variance in male EPRS and fitness. 3. We then used 20 years of complete genetic paternity and pedigree data from wild song sparrows (Melospiza melodia) to partition variance in each of the three subcomponents of EPRS, and thereby estimate their additive genetic variance and heritability conditioned on effects of male coefficient of inbreeding, age and social status. 4. All three subcomponents of EPRS showed some degree of within-male repeatability, reflecting combined permanent environmental and genetic effects. Number of available broods and offspring per brood showed low additive genetic variances. The estimated additive genetic variance in extra-pair siring probability was larger, although the 95% credible interval still converged towards zero. Siring probability also showed inbreeding depression and increased with male age

  18. 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

  19. A relation between information entropy and variance

    CERN Document Server

    Pandey, Biswajit

    2016-01-01

    We obtain an analytic relation between the information entropy and the variance of a distribution in the regime of small fluctuations. We use a set of Monte Carlo simulations of different homogeneous and inhomogeneous distributions to verify the relation and also test it in a set of cosmological N-body simulations. We find that the relation is in excellent agreement with the simulations and is independent of number density and the nature of the distributions. The relation would help us to relate entropy to other conventional measures and widen its scope.

  20. 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...

  1. Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

    Science.gov (United States)

    Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.

    2012-10-01

    The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme

  2. EXPLANATORY VARIANCE IN MAXIMAL OXYGEN UPTAKE

    Directory of Open Access Journals (Sweden)

    Jacalyn J. Robert McComb

    2006-06-01

    Full Text Available The purpose of this study was to develop a prediction equation that could be used to estimate maximal oxygen uptake (VO2max from a submaximal water running protocol. Thirty-two volunteers (n =19 males, n = 13 females, ages 18 - 24 years, underwent the following testing procedures: (a a 7-site skin fold assessment; (b a land VO2max running treadmill test; and (c a 6 min water running test. For the water running submaximal protocol, the participants were fitted with an Aqua Jogger Classic Uni-Sex Belt and a Polar Heart Rate Monitor; the participants' head, shoulders, hips and feet were vertically aligned, using a modified running/bicycle motion. A regression model was used to predict VO2max. The criterion variable, VO2max, was measured using open-circuit calorimetry utilizing the Bruce Treadmill Protocol. Predictor variables included in the model were percent body fat (% BF, height, weight, gender, and heart rate following a 6 min water running protocol. Percent body fat accounted for 76% (r = -0.87, SEE = 3.27 of the variance in VO2max. No other variables significantly contributed to the explained variance in VO2max. The equation for the estimation of VO2max is as follows: VO2max ml.kg-1·min-1 = 56.14 - 0.92 (% BF.

  3. Dimension reduction based on weighted variance estimate

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    In this paper, we propose a new estimate for dimension reduction, called the weighted variance estimate (WVE), which includes Sliced Average Variance Estimate (SAVE) as a special case. Bootstrap method is used to select the best estimate from the WVE and to estimate the structure dimension. And this selected best estimate usually performs better than the existing methods such as Sliced Inverse Regression (SIR), SAVE, etc. Many methods such as SIR, SAVE, etc. usually put the same weight on each observation to estimate central subspace (CS). By introducing a weight function, WVE puts different weights on different observations according to distance of observations from CS. The weight function makes WVE have very good performance in general and complicated situations, for example, the distribution of regressor deviating severely from elliptical distribution which is the base of many methods, such as SIR, etc. And compared with many existing methods, WVE is insensitive to the distribution of the regressor. The consistency of the WVE is established. Simulations to compare the performances of WVE with other existing methods confirm the advantage of WVE.

  4. Dimension reduction based on weighted variance estimate

    Institute of Scientific and Technical Information of China (English)

    ZHAO JunLong; XU XingZhong

    2009-01-01

    In this paper,we propose a new estimate for dimension reduction,called the weighted variance estimate (WVE),which includes Sliced Average Variance Estimate (SAVE) as a special case.Bootstrap method is used to select the best estimate from the WVE and to estimate the structure dimension.And this selected best estimate usually performs better than the existing methods such as Sliced Inverse Regression (SIR),SAVE,etc.Many methods such as SIR,SAVE,etc.usually put the same weight on each observation to estimate central subspace (CS).By introducing a weight function,WVE puts different weights on different observations according to distance of observations from CS.The weight function makes WVE have very good performance in general and complicated situations,for example,the distribution of regressor deviating severely from elliptical distribution which is the base of many methods,such as SIR,etc.And compared with many existing methods,WVE is insensitive to the distribution of the regressor.The consistency of the WVE is established.Simulations to compare the performances of WVE with other existing methods confirm the advantage of WVE.

  5. Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in Terms of Phenotypic Variances

    Science.gov (United States)

    Kaneko, Kunihiko

    2012-09-01

    The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The relationship suggests a link between robustness to noise and to mutation, since robustness can be defined by the sharpness of the distribution of the phenotype. Next, the proportionality between the variances is demonstrated to also hold over expressions of different genes (phenotypic traits) when the system acquires robustness through the evolution. Then, evolution under environmental variation is numerically investigated and it is found that both the adaptability to a novel environment and the robustness are made compatible when a certain degree of phenotypic fluctuations exists due to noise. The highest adaptability is achieved at a certain noise level at which the gene expression dynamics are near the critical state to lose the robustness. Based on our results, we revisit Waddington's canalization and genetic assimilation with regard to the two types of phenotypic fluctuations.

  6. Fuzzy cross-entropy, mean, variance, skewness models for portfolio selection

    Directory of Open Access Journals (Sweden)

    Rupak Bhattacharyya

    2014-01-01

    Full Text Available In this paper, fuzzy stock portfolio selection models that maximize mean and skewness as well as minimize portfolio variance and cross-entropy are proposed. Because returns are typically asymmetric, in addition to typical mean and variance considerations, third order moment skewness is also considered in generating a larger payoff. Cross-entropy is used to quantify the level of discrimination in a return for a given satisfactory return value. As returns are uncertain, stock returns are considered triangular fuzzy numbers. Stock price data from the Bombay Stock Exchange are used to illustrate the effectiveness of the proposed model. The solutions are done by genetic algorithms.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    traits such as mammary disease traits in dairy cattle. METHODS: Data on progeny means of six traits related to mastitis resistance in dairy cattle (general mastitis resistance and five pathogen-specific mastitis resistance traits) were analyzed using a bivariate Bayesian SNP-based genomic model......)variances of mastitis resistance traits in dairy cattle using multivariate genomic models......., per chromosome, and in regions of 100 SNP on a chromosome. RESULTS: Genomic proportions of the total variance differed between traits. Genomic correlations were lower than pedigree-based genetic correlations and they were highest between general mastitis and pathogen-specific traits because...

  8. A Mean-variance Problem in the Constant Elasticity of Variance (CEV) Mo del

    Institute of Scientific and Technical Information of China (English)

    Hou Ying-li; Liu Guo-xin; Jiang Chun-lan

    2015-01-01

    In this paper, we focus on a constant elasticity of variance (CEV) model and want to find its optimal strategies for a mean-variance problem under two con-strained controls: reinsurance/new business and investment (no-shorting). First, a Lagrange multiplier is introduced to simplify the mean-variance problem and the corresponding Hamilton-Jacobi-Bellman (HJB) equation is established. Via a power transformation technique and variable change method, the optimal strategies with the Lagrange multiplier are obtained. Final, based on the Lagrange duality theorem, the optimal strategies and optimal value for the original problem (i.e., the efficient strategies and efficient frontier) are derived explicitly.

  9. Extreme patterns of variance in small populations: placing limits on human Y-chromosome diversity through time in the Vanuatu Archipelago.

    Science.gov (United States)

    Cox, M

    2007-05-01

    Small populations are dominated by unique patterns of variance, largely characterized by rapid drift of allele frequencies. Although the variance components of genetic datasets have long been recognized, most population genetic studies still treat all sampling locations equally despite differences in sampling and effective population sizes. Because excluding the effects of variance can lead to significant biases in historical reconstruction, variance components should be incorporated explicitly into population genetic analyses. The possible magnitude of variance effects in small populations is illustrated here via a case study of Y-chromosome haplogroup diversity in the Vanuatu Archipelago. Deme-based modelling is used to simulate allele frequencies through time, and conservative confidence bounds are placed on the accumulation of stochastic variance effects, including diachronic genetic drift and contemporary sampling error. When the information content of the dataset has been ascertained, demographic models with parameters falling outside the confidence bounds of the variance components can then be accepted with some statistical confidence. Here I emphasize how aspects of the demographic history of a population can be disentangled from stochastic variance effects, and I illustrate the extreme roles of genetic drift and sampling error for many small human population datasets.

  10. 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 realized variances, our model allows to infer the occurrence and size of extreme variance events, and construct indicators signalling agents sentiment towards future market conditions. Our results show that excess returns are to a large extent explained by fear or optimism towards future extreme variance...

  11. The value of travel time variance

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Engelson, Leonid

    2011-01-01

    This paper considers the value of travel time variability under scheduling preferences that are defined 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 freely choose departure time and to travellers who use a scheduled service with fixed headway. Depending...... on parameters, travellers may be risk averse or risk seeking and the value of travel time may increase or decrease in the mean travel time....

  12. Power Estimation in Multivariate Analysis of Variance

    Directory of Open Access Journals (Sweden)

    Jean François Allaire

    2007-09-01

    Full Text Available Power is often overlooked in designing multivariate studies for the simple reason that it is believed to be too complicated. In this paper, it is shown that power estimation in multivariate analysis of variance (MANOVA can be approximated using a F distribution for the three popular statistics (Hotelling-Lawley trace, Pillai-Bartlett trace, Wilk`s likelihood ratio. Consequently, the same procedure, as in any statistical test, can be used: computation of the critical F value, computation of the noncentral parameter (as a function of the effect size and finally estimation of power using a noncentral F distribution. Various numerical examples are provided which help to understand and to apply the method. Problems related to post hoc power estimation are discussed.

  13. Expected Stock Returns and Variance Risk Premia

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Tauchen, George; Zhou, Hao

    Motivated by the implications from a stylized self-contained general equilibrium model incorporating the effects of time-varying economic uncertainty, we show that the difference between implied and realized variation, or the variance risk premium, is able to explain a non-trivial fraction...... of the time series variation in post 1990 aggregate stock market returns, with high (low) premia predicting high (low) future returns. Our empirical results depend crucially on the use of "model-free," as opposed to Black- Scholes, options implied volatilities, along with accurate realized variation measures...... constructed from high-frequency intraday, as opposed to daily, data. The magnitude of the predictability is particularly strong at the intermediate quarterly return horizon, where it dominates that afforded by other popular predictor variables, like the P/E ratio, the default spread, and the consumption...

  14. Components of variance and heritability of resistance to important fungal diseases agents in grapevine

    Directory of Open Access Journals (Sweden)

    Nikolić Dragan

    2006-01-01

    Full Text Available In four interspecies crossing combinations of grapevine (Seedling 108 x Muscat Hamburg, Muscat Hamburg x Seedling 108, S.V.I8315 x Muscat Hamburg and Muscat Hamburg x S.V.I2375 during three years period, resistance to important fungal diseases agents (Plasmopara viticola and Botrytis cinerea were examined. Based on results of analysis of variance, for investigated characteristics, components of variance, coefficients of genetic and phenotypic variation and coefficient of heritability in a broader sense were calculated. It was established that for both characteristics and in all crossing combinations, genetic variance took the biggest part in total variability. The lowest coefficients of genetic and phenotypic variation were established for both properties in crossing combination Seedling 108 x Muscat Hamburg. The highest coefficients of genetic and phenotypic variation were determined for leaf resistance to Plasmopara viticola in crossing combination Muscat Hamburg x S.V.I2375, and for bunch resistance to Botrytis cinerea in crossing combination Muscat Hamburg x Seedling 108. Considering all investigated crossing combinations, coefficient of heritability for leaf resistance to Plasmopara viticola was from 87.23% to 94.88%, and for bunch resistance to Botrytis cinerea from 88.04% to 93.32%. .

  15. The Parabolic Variance (PVAR): A Wavelet Variance Based on the Least-Square Fit.

    Science.gov (United States)

    Vernotte, Francois; Lenczner, Michel; Bourgeois, Pierre-Yves; Rubiola, Enrico

    2016-04-01

    This paper introduces the parabolic variance (PVAR), a wavelet variance similar to the Allan variance (AVAR), based on the linear regression (LR) of phase data. The companion article arXiv:1506.05009 [physics.ins-det] details the Ω frequency counter, which implements the LR estimate. The PVAR combines the advantages of AVAR and modified AVAR (MVAR). PVAR is good for long-term analysis because the wavelet spans over 2τ, the same as the AVAR wavelet, and good for short-term analysis because the response to white and flicker PM is 1/τ(3) and 1/τ(2), the same as the MVAR. After setting the theoretical framework, we study the degrees of freedom and the confidence interval for the most common noise types. Then, we focus on the detection of a weak noise process at the transition-or corner-where a faster process rolls off. This new perspective raises the question of which variance detects the weak process with the shortest data record. Our simulations show that PVAR is a fortunate tradeoff. PVAR is superior to MVAR in all cases, exhibits the best ability to divide between fast noise phenomena (up to flicker FM), and is almost as good as AVAR for the detection of random walk and drift.

  16. A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships.

    Science.gov (United States)

    Visscher, Peter M; Goddard, Michael E

    2015-01-01

    Heritability is a population parameter of importance in evolution, plant and animal breeding, and human medical genetics. It can be estimated using pedigree designs and, more recently, using relationships estimated from markers. We derive the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation. We show that well-known results for balanced designs are special cases of a more general unified framework. For pedigree designs, the sampling variance is inversely proportional to the variance of relationship in the pedigree and it is proportional to 1/N, whereas for population samples it is approximately proportional to 1/N(2), where N is the sample size. Variation in relatedness is a key parameter in the quantification of the sampling variance of heritability. Consequently, the sampling variance is high for populations with large recent effective population size (e.g., humans) because this causes low variation in relationship. However, even using human population samples, low sampling variance is possible with high N. Copyright © 2015 by the Genetics Society of America.

  17. Restricted maximum likelihood estimation of variance components from field data for number of pigs born alive.

    Science.gov (United States)

    See, M T; Mabry, J W; Bertrand, J K

    1993-11-01

    Variance components for number of pigs born alive (NBA) were estimated from sow productivity field records collected by purebred breed associations. Data sets analyzed were as follows: Hampshire (n = 13,537), Landrace (n = 10,822), and Spotted (n = 3,949). Variance components for service sire, sire of sow, dam of sow, and residual effects on NBA (adjusted for parity) were estimated. The single-trait model included relationships between service sires, sires of sows, and dams of sows. The model was implemented using an expectation maximization (EM) REML algorithm. A sparse-matrix solver was also used. Heritability estimates for NBA were .13, .13, and .12 for Hampshire, Spotted, and Landrace, respectively. Estimates of maternal genetic (co)variances (m2) expressed as a proportion of the phenotypic variance were .05, .01, and .03 for Hampshire, Spotted, and Landrace, respectively. Results indicated that service sires account for 1 to 2% of the total variation for NBA. Genetic effects influencing NBA seem to be small in these data sets, but selection for increased NBA should be effective.

  18. Bivariate genetic modeling of cardiovascular stress reactivity : Does stress uncover genetic variance?

    NARCIS (Netherlands)

    De Geus, Eco J. C.; Kupper, Nina; Boomsma, Dorret I.; Snieder, Harold

    2007-01-01

    Objective: To test the existence of gene-by-stress interaction by assessing cardiovascular stress reactivity in monozygotic and dizygotic twins. Methods: We studied 160 adolescent (mean age 16.7 +/- 2.0 years; range 13-22 years) and 212 middle-aged twin pairs (mean age 44.2 +/- 6.7 years; range 34-6

  19. Genomic variance estimates: With or without disequilibrium covariances?

    Science.gov (United States)

    Lehermeier, C; de Los Campos, G; Wimmer, V; Schön, C-C

    2017-06-01

    Whole-genome regression methods are often used for estimating genomic heritability: the proportion of phenotypic variance that can be explained by regression on marker genotypes. Recently, there has been an intensive debate on whether and how to account for the contribution of linkage disequilibrium (LD) to genomic variance. Here, we investigate two different methods for genomic variance estimation that differ in their ability to account for LD. By analysing flowering time in a data set on 1,057 fully sequenced Arabidopsis lines with strong evidence for diversifying selection, we observed a large contribution of covariances between quantitative trait loci (QTL) to the genomic variance. The classical estimate of genomic variance that ignores covariances underestimated the genomic variance in the data. The second method accounts for LD explicitly and leads to genomic variance estimates that when added to error variance estimates match the sample variance of phenotypes. This method also allows estimating the covariance between sets of markers when partitioning the genome into subunits. Large covariance estimates between the five Arabidopsis chromosomes indicated that the population structure in the data led to strong LD also between physically unlinked QTL. By consecutively removing population structure from the phenotypic variance using principal component analysis, we show how population structure affects the magnitude of LD contribution and the genomic variance estimates obtained with the two methods. © 2017 Blackwell Verlag GmbH.

  20. Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

    Science.gov (United States)

    Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

    2016-04-01

    Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity.

  1. Variance components estimation for farrowing traits of three purebred pigs in Korea

    Directory of Open Access Journals (Sweden)

    Bryan Irvine Lopez

    2017-09-01

    Full Text Available Objective This study was conducted to estimate breed-specific variance components for total number born (TNB, number born alive (NBA and mortality rate from birth through weaning including stillbirths (MORT of three main swine breeds in Korea. In addition, the importance of including maternal genetic and service sire effects in estimation models was evaluated. Methods Records of farrowing traits from 6,412 Duroc, 18,020 Landrace, and 54,254 Yorkshire sows collected from January 2001 to September 2016 from different farms in Korea were used in the analysis. Animal models and the restricted maximum likelihood method were used to estimate variances in animal genetic, permanent environmental, maternal genetic, service sire and residuals. Results The heritability estimates ranged from 0.072 to 0.102, 0.090 to 0.099, and 0.109 to 0.121 for TNB; 0.087 to 0.110, 0.088 to 0.100, and 0.099 to 0.107 for NBA; and 0.027 to 0.031, 0.050 to 0.053, and 0.073 to 0.081 for MORT in the Duroc, Landrace and Yorkshire breeds, respectively. The proportion of the total variation due to permanent environmental effects, maternal genetic effects, and service sire effects ranged from 0.042 to 0.088, 0.001 to 0.031, and 0.001 to 0.021, respectively. Spearman rank correlations among models ranged from 0.98 to 0.99, demonstrating that the maternal genetic and service sire effects have small effects on the precision of the breeding value. Conclusion Models that include additive genetic and permanent environmental effects are suitable for farrowing traits in Duroc, Landrace, and Yorkshire populations in Korea. This breed-specific variance components estimates for litter traits can be utilized for pig improvement programs in Korea.

  2. Variance components estimation for farrowing traits of three purebred pigs in Korea.

    Science.gov (United States)

    Lopez, Bryan Irvine; Kim, Tae Hun; Makumbe, Milton Tinashe; Song, Chol Won; Seo, Kang Seok

    2017-09-01

    This study was conducted to estimate breed-specific variance components for total number born (TNB), number born alive (NBA) and mortality rate from birth through weaning including stillbirths (MORT) of three main swine breeds in Korea. In addition, the importance of including maternal genetic and service sire effects in estimation models was evaluated. Records of farrowing traits from 6,412 Duroc, 18,020 Landrace, and 54,254 Yorkshire sows collected from January 2001 to September 2016 from different farms in Korea were used in the analysis. Animal models and the restricted maximum likelihood method were used to estimate variances in animal genetic, permanent environmental, maternal genetic, service sire and residuals. The heritability estimates ranged from 0.072 to 0.102, 0.090 to 0.099, and 0.109 to 0.121 for TNB; 0.087 to 0.110, 0.088 to 0.100, and 0.099 to 0.107 for NBA; and 0.027 to 0.031, 0.050 to 0.053, and 0.073 to 0.081 for MORT in the Duroc, Landrace and Yorkshire breeds, respectively. The proportion of the total variation due to permanent environmental effects, maternal genetic effects, and service sire effects ranged from 0.042 to 0.088, 0.001 to 0.031, and 0.001 to 0.021, respectively. Spearman rank correlations among models ranged from 0.98 to 0.99, demonstrating that the maternal genetic and service sire effects have small effects on the precision of the breeding value. Models that include additive genetic and permanent environmental effects are suitable for farrowing traits in Duroc, Landrace, and Yorkshire populations in Korea. This breed-specific variance components estimates for litter traits can be utilized for pig improvement programs in Korea.

  3. Estimation of additive and dominance variance for reproductive traits from different models in Duroc purebred

    OpenAIRE

    Talerngsak Angkuraseranee

    2010-01-01

    The additive and dominance genetic variances of 5,801 Duroc reproductive and growth records were estimated usingBULPF90 PC-PACK. Estimates were obtained for number born alive (NBA), birth weight (BW), number weaned (NW), andweaning weight (WW). Data were analyzed using two mixed model equations. The first model included fixed effects andrandom effects identifying inbreeding depression, additive gene effect and permanent environments effects. The secondmodel was similar to the first model, but...

  4. Proportionality between variances in gene expression induced by noise and mutation: consequence of evolutionary robustness

    Directory of Open Access Journals (Sweden)

    Kaneko Kunihiko

    2011-01-01

    Full Text Available Abstract Background Characterization of robustness and plasticity of phenotypes is a basic issue in evolutionary and developmental biology. The robustness and plasticity are concerned with changeability of a biological system against external perturbations. The perturbations are either genetic, i.e., due to mutations in genes in the population, or epigenetic, i.e., due to noise during development or environmental variations. Thus, the variances of phenotypes due to genetic and epigenetic perturbations provide quantitative measures for such changeability during evolution and development, respectively. Results Using numerical models simulating the evolutionary changes in the gene regulation network required to achieve a particular expression pattern, we first confirmed that gene expression dynamics robust to mutation evolved in the presence of a sufficient level of transcriptional noise. Under such conditions, the two types of variances in the gene expression levels, i.e. those due to mutations to the gene regulation network and those due to noise in gene expression dynamics were found to be proportional over a number of genes. The fraction of such genes with a common proportionality coefficient increased with an increase in the robustness of the evolved network. This proportionality was generally confirmed, also under the presence of environmental fluctuations and sexual recombination in diploids, and was explained from an evolutionary robustness hypothesis, in which an evolved robust system suppresses the so-called error catastrophe - the destabilization of the single-peaked distribution in gene expression levels. Experimental evidences for the proportionality of the variances over genes are also discussed. Conclusions The proportionality between the genetic and epigenetic variances of phenotypes implies the correlation between the robustness (or plasticity against genetic changes and against noise in development, and also suggests that

  5. 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...... reproductive skew with decreasing size variation among males under natural conditions. (c) 2006 The Author Journal compilation (c) 2006 The Fisheries Society of the British Isles...

  6. Gene set analysis using variance component tests

    Science.gov (United States)

    2013-01-01

    Background Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. Results We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). Conclusion We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data. PMID:23806107

  7. Anatomic variance of the iliopsoas tendon.

    Science.gov (United States)

    Philippon, Marc J; Devitt, Brian M; Campbell, Kevin J; Michalski, Max P; Espinoza, Chris; Wijdicks, Coen A; Laprade, Robert F

    2014-04-01

    The iliopsoas tendon has been implicated as a generator of hip pain and a cause of labral injury due to impingement. Arthroscopic release of the iliopsoas tendon has become a preferred treatment for internal snapping hips. Traditionally, the iliopsoas tendon has been considered the conjoint tendon of the psoas major and iliacus muscles, although anatomic variance has been reported. The iliopsoas tendon consists of 2 discrete tendons in the majority of cases, arising from both the psoas major and iliacus muscles. Descriptive laboratory study. Fifty-three nonmatched, fresh-frozen, cadaveric hemipelvis specimens (average age, 62 years; range, 47-70 years; 29 male and 24 female) were used in this study. The iliopsoas muscle was exposed via a Smith-Petersen approach. A transverse incision across the entire iliopsoas musculotendinous unit was made at the level of the hip joint. Each distinctly identifiable tendon was recorded, and the distance from the lesser trochanter was recorded. The prevalence of a single-, double-, and triple-banded iliopsoas tendon was 28.3%, 64.2%, and 7.5%, respectively. The psoas major tendon was consistently the most medial tendinous structure, and the primary iliacus tendon was found immediately lateral to the psoas major tendon within the belly of the iliacus muscle. When present, an accessory iliacus tendon was located adjacent to the primary iliacus tendon, lateral to the primary iliacus tendon. Once considered a rare anatomic variant, the finding of ≥2 distinct tendinous components to the iliacus and psoas major muscle groups is an important discovery. It is essential to be cognizant of the possibility that more than 1 tendon may exist to ensure complete release during endoscopy. Arthroscopic release of the iliopsoas tendon is a well-accepted surgical treatment for iliopsoas impingement. The most widely used site for tendon release is at the level of the anterior hip joint. The findings of this novel cadaveric anatomy study suggest that

  8. 40 CFR 190.11 - Variances for unusual operations.

    Science.gov (United States)

    2010-07-01

    ... PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  9. Simulations of the Hadamard Variance: Probability Distributions and Confidence Intervals.

    Science.gov (United States)

    Ashby, Neil; Patla, Bijunath

    2016-04-01

    Power-law noise in clocks and oscillators can be simulated by Fourier transforming a modified spectrum of white phase noise. This approach has been applied successfully to simulation of the Allan variance and the modified Allan variance in both overlapping and nonoverlapping forms. When significant frequency drift is present in an oscillator, at large sampling times the Allan variance overestimates the intrinsic noise, while the Hadamard variance is insensitive to frequency drift. The simulation method is extended in this paper to predict the Hadamard variance for the common types of power-law noise. Symmetric real matrices are introduced whose traces-the sums of their eigenvalues-are equal to the Hadamard variances, in overlapping or nonoverlapping forms, as well as for the corresponding forms of the modified Hadamard variance. We show that the standard relations between spectral densities and Hadamard variance are obtained with this method. The matrix eigenvalues determine probability distributions for observing a variance at an arbitrary value of the sampling interval τ, and hence for estimating confidence in the measurements.

  10. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Directory of Open Access Journals (Sweden)

    Ashton M Verdery

    Full Text Available 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.

  11. 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.

  12. 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.

  13. Estimation of Variance Components for Litter Size in the First and Later Parities in Improved Jezersko-Solcava Sheep

    Directory of Open Access Journals (Sweden)

    Dubravko Škorput

    2011-12-01

    Full Text Available Aim of this study was to estimate variance components for litter size in Improved Jezersko-Solcava sheep. Analysis involved 66,082 records from 12,969 animals, for the number of lambs born in all parities (BA, the first parity (B1, and later parities (B2+. Fixed part of model contained the effects of season and age at lambing within parity. Random part of model contained the effects of herd, permanent effect (for repeatability models, and additive genetic effect. Variance components were estimated using the restricted maximum likelihood method. The average number of lambs born was 1.36 in the first parity, while the average in later parities was 1.59 leading also to about 20% higher variance. Several models were tested in order to accommodate markedly different variability in litter size between the first and later parities: single trait model (for BA, B1, and B2+, two-trait model (for B1 and B2+, and single trait model with heterogeneous residual variance (for BA. Comparison of variance components between models showed largest differences for the residual variance, resulting in parsimonious fit for a single trait model for BA with heterogeneous residual variance. Correlations among breeding values from different models were high and showed remarkable performance of the standard single trait repeatability model for BA.

  14. The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP.

    Science.gov (United States)

    Totir, Liviu R; Fernando, Rohan L; Dekkers, Jack C M; Fernández, Soledad A; Guldbrandtsen, Bernt

    2004-01-01

    Under additive inheritance, the Henderson mixed model equations (HMME) provide an efficient approach to obtaining genetic evaluations by marker assisted best linear unbiased prediction (MABLUP) given pedigree relationships, trait and marker data. For large pedigrees with many missing markers, however, it is not feasible to calculate the exact gametic variance covariance matrix required to construct HMME. The objective of this study was to investigate the consequences of using approximate gametic variance covariance matrices on response to selection by MABLUP. Two methods were used to generate approximate variance covariance matrices. The first method (Method A) completely discards the marker information for individuals with an unknown linkage phase between two flanking markers. The second method (Method B) makes use of the marker information at only the most polymorphic marker locus for individuals with an unknown linkage phase. Data sets were simulated with and without missing marker data for flanking markers with 2, 4, 6, 8 or 12 alleles. Several missing marker data patterns were considered. The genetic variability explained by marked quantitative trait loci (MQTL) was modeled with one or two MQTL of equal effect. Response to selection by MABLUP using Method A or Method B were compared with that obtained by MABLUP using the exact genetic variance covariance matrix, which was estimated using 15,000 samples from the conditional distribution of genotypic values given the observed marker data. For the simulated conditions, the superiority of MABLUP over BLUP based only on pedigree relationships and trait data varied between 0.1% and 13.5% for Method A, between 1.7% and 23.8% for Method B, and between 7.6% and 28.9% for the exact method. The relative performance of the methods under investigation was not affected by the number of MQTL in the model.

  15. Analysis of variance of designed chromatographic data sets: The analysis of variance-target projection approach.

    Science.gov (United States)

    Marini, Federico; de Beer, Dalene; Joubert, Elizabeth; Walczak, Beata

    2015-07-31

    Direct application of popular approaches, e.g., Principal Component Analysis (PCA) or Partial Least Squares (PLS) to chromatographic data originating from a well-designed experimental study including more than one factor is not recommended. In the case of a well-designed experiment involving two or more factors (crossed or nested), data are usually decomposed into the contributions associated with the studied factors (and with their interactions), and the individual effect matrices are then analyzed using, e.g., PCA, as in the case of ASCA (analysis of variance combined with simultaneous component analysis). As an alternative to the ASCA method, we propose the application of PLS followed by target projection (TP), which allows a one-factor representation of the model for each column in the design dummy matrix. PLS application follows after proper deflation of the experimental matrix, i.e., to what are called the residuals under the reduced ANOVA model. The proposed approach (ANOVA-TP) is well suited for the study of designed chromatographic data of complex samples. It allows testing of statistical significance of the studied effects, 'biomarker' identification, and enables straightforward visualization and accurate estimation of between- and within-class variance. The proposed approach has been successfully applied to a case study aimed at evaluating the effect of pasteurization on the concentrations of various phenolic constituents of rooibos tea of different quality grades and its outcomes have been compared to those of ASCA.

  16. An Analysis of Variance Framework for Matrix Sampling.

    Science.gov (United States)

    Sirotnik, Kenneth

    Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

  17. 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…

  18. 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…

  19. Error Variance of Rasch Measurement with Logistic Ability Distributions.

    Science.gov (United States)

    Dimitrov, Dimiter M.

    Exact formulas for classical error variance are provided for Rasch measurement with logistic distributions. An approximation formula with the normal ability distribution is also provided. With the proposed formulas, the additive contribution of individual items to the population error variance can be determined without knowledge of the other test…

  20. A Broadband Beamformer Using Controllable Constraints and Minimum Variance

    DEFF Research Database (Denmark)

    Karimian-Azari, Sam; Benesty, Jacob; Jensen, Jesper Rindom

    2014-01-01

    The minimum variance distortionless response (MVDR) and the linearly constrained minimum variance (LCMV) beamformers are two optimal approaches in the sense of noise reduction. The LCMV beamformer can also reject interferers using linear constraints at the expense of reducing the degree of freedom...

  1. 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…

  2. Delivery Time Variance Reduction in the Military Supply Chain

    Science.gov (United States)

    2010-03-01

    DELIVERY TIME VARIANCE REDUCTION IN THE MILITARY SUPPLY CHAIN THESIS...IN THE MILITARY SUPPLY CHAIN THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering...March 2010 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-OR-MS-ENS-10-02 DELIVERY TIME VARIANCE IN THE MILITARY SUPPLY CHAIN Preston

  3. The asymptotic variance of departures in critically loaded queues

    NARCIS (Netherlands)

    A. Al Hanbali; M.R.H. Mandjes (Michel); Y. Nazarathy (Yoni); W. Whitt

    2010-01-01

    htmlabstractWe 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 that the system load rho equals 1, and prove that the asymptotic variance rate satisfies lim_t Var D(t)/t = lambda

  4. 76 FR 78698 - Proposed Revocation of Permanent Variances

    Science.gov (United States)

    2011-12-19

    ... Occupational Safety and Health Administration Proposed Revocation of Permanent Variances AGENCY: Occupational... short and plain statement detailing (1) how the proposed revocation would affect the requesting party..., subpart L. The following table provides information about the variances proposed for revocation by...

  5. Adjustment for heterogeneous variances due to days in milk and ...

    African Journals Online (AJOL)

    ARC-IRENE

    Adjustment of heterogeneous variances and a calving year effect in test-day ... Regression Test-Day Model (FRTDM), which assumes equal variances of the response variable at different .... random residual error .... records were included in the selection, while in the unadjusted data set, lactations consisting of six and more.

  6. Productive Failure in Learning the Concept of Variance

    Science.gov (United States)

    Kapur, Manu

    2012-01-01

    In a study with ninth-grade mathematics students on learning the concept of variance, students experienced either direct instruction (DI) or productive failure (PF), wherein they were first asked to generate a quantitative index for variance without any guidance before receiving DI on the concept. Whereas DI students relied only on the canonical…

  7. Time variance effects and measurement error indications for MLS measurements

    DEFF Research Database (Denmark)

    Liu, Jiyuan

    1999-01-01

    Mathematical characteristics of Maximum-Length-Sequences are discussed, and effects of measuring on slightly time-varying systems with the MLS method are examined with computer simulations with MATLAB. A new coherence measure is suggested for the indication of time-variance effects. The results...... of the simulations show that the proposed MLS coherence can give an indication of time-variance effects....

  8. Confidence Intervals of Variance Functions in Generalized Linear Model

    Institute of Scientific and Technical Information of China (English)

    Yong Zhou; Dao-ji Li

    2006-01-01

    In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models (GLMs), when designs are fixed points and random variables respectively. Bias-corrected confidence bands are proposed for the (conditional) variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the (conditional) variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparametric autoregressive times series model with heteroscedastic conditional variance.

  9. Research on variance of subnets in network sampling

    Institute of Scientific and Technical Information of China (English)

    Qi Gao; Xiaoting Li; Feng Pan

    2014-01-01

    In the recent research of network sampling, some sam-pling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as wel as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor (CNN) model, random network and smal-world network to explore the variance in network sam-pling. As proved by the results, snowbal sampling obtains the most variance of subnets, but does wel in capturing the network struc-ture. The variance of networks sampled by the hub and random strategy are much smal er. The hub strategy performs wel in re-flecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.

  10. 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.

  11. The genetics of obesity.

    Science.gov (United States)

    All definitions of the metabolic syndrome include some form of obesity as one of the possible features. Body mass index (BMI) has a known genetic component, currently estimated to account for about 70% of the population variance in weight status for non-syndromal obesity. Much research effort has be...

  12. Genetic variation in variability

    NARCIS (Netherlands)

    Mulder, Herman; Gienapp, Phillip; Visser, Marcel E.

    2016-01-01

    Variation in traits is essential for natural selection to operate and genetic and environmental effects can contribute to this phenotypic variation. From domesticated populations, we know that families can differ in their level of within-family variance, which leads to the intriguing situation th

  13. Utility functions predict variance and skewness risk preferences in monkeys.

    Science.gov (United States)

    Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

    2016-07-26

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

  14. The genetics of maternal care: direct and indirect genetic effects on phenotype in the dung beetle Onthophagus taurus.

    Science.gov (United States)

    Hunt, John; Simmons, Leigh W

    2002-05-14

    While theoretical models of the evolution of parental care are based on the assumption of underlying genetic variance, surprisingly few quantitative genetic studies of this life-history trait exist. Estimation of the degree of genetic variance in parental care is important because it can be a significant source of maternal effects, which, if genetically based, represent indirect genetic effects. A major prediction of indirect genetic effect theory is that traits without heritable variation can evolve because of the heritable environmental variation that indirect genetic effects provide. In the dung beetle, Onthophagus taurus, females provide care to offspring by provisioning a brood mass. The size of the brood mass has pronounced effects on offspring phenotype. Using a half-sib breeding design we show that the weight of the brood mass females produce exhibits significant levels of additive genetic variance due to sires. However, variance caused by dams is considerably larger, demonstrating that maternal effects are also important. Body size exhibited low additive genetic variance. However, body size exerts a strong maternal influence on the weight of brood masses produced, accounting for 22% of the nongenetic variance in offspring body size. Maternal body size also influenced the number of offspring produced but there was no genetic variance for this trait. Offspring body size and brood mass weight exhibited positive genetic and phenotypic correlations. We conclude that both indirect genetic effects, via maternal care, and nongenetic maternal effects, via female size, play important roles in the evolution of phenotype in this species.

  15. The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations.

    Science.gov (United States)

    Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng

    2017-03-15

    With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained variance and covariance for milk yield and fat yield, and explained variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables

  16. Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

    NARCIS (Netherlands)

    Hickey, J.M.; Veerkamp, R.F.; Calus, M.P.L.; Mulder, H.A.; Thompson, R.

    2009-01-01

    Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo

  17. Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

    NARCIS (Netherlands)

    Hickey, J.M.; Veerkamp, R.F.; Calus, M.P.L.; Mulder, H.A.; Thompson, R.

    2009-01-01

    Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sam

  18. Variance and covariance of actual relationships between relatives at one locus.

    Science.gov (United States)

    Garcia-Cortes, Luis Alberto; Legarra, Andres; Chevalet, Claude; Toro, Miguel Angel

    2013-01-01

    The relationship between pairs of individuals is an important topic in many areas of population and quantitative genetics. It is usually measured as the proportion of the genome identical by descent shared by the pair and it can be inferred from pedigree information. But there is a variance in actual relationships as a consequence of mendelian sampling, whose general formula has not been developed. The goal of this work is to develop this general formula for the one-locus situation,. We provide simple expressions for the variances and covariances of all actual relationships in an arbitrary complex pedigree. The proposed method relies on the use of the nine identity coefficients and the generalized relationship coefficients; formulas have been checked by computer simulation. Finally two examples for a short pedigree of dogs and a long pedigree of sheep are given.

  19. 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 ...... 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....... 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......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...

  20. Filtered kriging for spatial data with heterogeneous measurement error variances.

    Science.gov (United States)

    Christensen, William F

    2011-09-01

    When predicting values for the measurement-error-free component of an observed spatial process, it is generally assumed that the process has a common measurement error variance. However, it is often the case that each measurement in a spatial data set has a known, site-specific measurement error variance, rendering the observed process nonstationary. We present a simple approach for estimating the semivariogram of the unobservable measurement-error-free process using a bias adjustment of the classical semivariogram formula. We then develop a new kriging predictor that filters the measurement errors. For scenarios where each site's measurement error variance is a function of the process of interest, we recommend an approach that also uses a variance-stabilizing transformation. The properties of the heterogeneous variance measurement-error-filtered kriging (HFK) predictor and variance-stabilized HFK predictor, and the improvement of these approaches over standard measurement-error-filtered kriging are demonstrated using simulation. The approach is illustrated with climate model output from the Hudson Strait area in northern Canada. In the illustration, locations with high or low measurement error variances are appropriately down- or upweighted in the prediction of the underlying process, yielding a realistically smooth picture of the phenomenon of interest.

  1. Meta-analysis of ratios of sample variances.

    Science.gov (United States)

    Prendergast, Luke A; Staudte, Robert G

    2016-05-20

    When conducting a meta-analysis of standardized mean differences (SMDs), it is common to use Cohen's d, or its variants, that require equal variances in the two arms of each study. While interpretation of these SMDs is simple, this alone should not be used as a justification for assuming equal variances. Until now, researchers have either used an F-test for each individual study or perhaps even conveniently ignored such tools altogether. In this paper, we propose a meta-analysis of ratios of sample variances to assess whether the equality of variances assumptions is justified prior to a meta-analysis of SMDs. Quantile-quantile plots, an omnibus test for equal variances or an overall meta-estimate of the ratio of variances can all be used to formally justify the use of less common methods when evidence of unequal variances is found. The methods in this paper are simple to implement and the validity of the approaches are reinforced by simulation studies and an application to a real data set.

  2. Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

    Science.gov (United States)

    Wu, Dong L.; Eckermann, Stephen D.

    2008-01-01

    The gravity wave (GW)-resolving capabilities of 118-GHz saturated thermal radiances acquired throughout the stratosphere by the Microwave Limb Sounder (MLS) on the Aura satellite are investigated and initial results presented. Because the saturated (optically thick) radiances resolve GW perturbations from a given altitude at different horizontal locations, variances are evaluated at 12 pressure altitudes between 21 and 51 km using the 40 saturated radiances found at the bottom of each limb scan. Forward modeling simulations show that these variances are controlled mostly by GWs with vertical wavelengths z 5 km and horizontal along-track wavelengths of y 100-200 km. The tilted cigar-shaped three-dimensional weighting functions yield highly selective responses to GWs of high intrinsic frequency that propagate toward the instrument. The latter property is used to infer the net meridional component of GW propagation by differencing the variances acquired from ascending (A) and descending (D) orbits. Because of improved vertical resolution and sensitivity, Aura MLS GW variances are 5?8 times larger than those from the Upper Atmosphere Research Satellite (UARS) MLS. Like UARS MLS variances, monthly-mean Aura MLS variances in January and July 2005 are enhanced when local background wind speeds are large, due largely to GW visibility effects. Zonal asymmetries in variance maps reveal enhanced GW activity at high latitudes due to forcing by flow over major mountain ranges and at tropical and subtropical latitudes due to enhanced deep convective generation as inferred from contemporaneous MLS cloud-ice data. At 21-28-km altitude (heights not measured by the UARS MLS), GW variance in the tropics is systematically enhanced and shows clear variations with the phase of the quasi-biennial oscillation, in general agreement with GW temperature variances derived from radiosonde, rocketsonde, and limb-scan vertical profiles.

  3. Variance components and heritabilities for sow productivity traits estimated from purebred versus crossbred sows.

    Science.gov (United States)

    Ehlers, M J; Mabry, J W; Bertrand, J K; Stalder, K J

    2005-10-01

    Genetic parameters were estimated for number of pigs born alive (NBA), adjusted litter weaning weight (ALWT), and the interval from weaning to first service (W2E) using 2002 purebred litter records and 14 583 crossbred litter records from a swine production unit with a defined great-grandparent, grandparent, and parent stock genetic system structure. Estimation of (co)variance components was carried out by REML methods. Heritability estimates from this study for NBA were 0.155, 0.146, 0.145 for the purebred, crossbred, and pooled data, respectively. Heritability estimates for ALWT were 0.162, 0.195, and 0.183 for the purebred, crossbred and pooled data, respectively. Heritability estimates for W2E were 0.205, 0.239 and 0.202 for the purebred, crossbred and pooled data, respectively. Genetic correlations between NBA and ALWT were weak and positive for the three groups. The genetic correlation between W2E and ALWT were -0.158 for the purebred Yorkshires, 0.031 for the crossbreds and 0.051 for the pooled data. The genetic correlation between W2E and NBA was -0.027 for the purebred Yorkshires, 0.310 for the crossbreds and 0.236 for the pooled data. These similarities suggest that pooling of purebred and crossbred data may be considered, which may potentially increase the accuracy of breeding value estimates, which would result in increased genetic progress.

  4. Variance and covariance components for liability of piglet survival during different periods.

    Science.gov (United States)

    Su, G; Sorensen, D; Lund, M S

    2008-02-01

    Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual piglet level, the estimates of direct heritability in Landrace were 0.035, 0.057 and 0.027, and in Yorkshire the estimates were 0.012, 0.030 and 0.025 for liability of survival at farrowing (SVB), from birth to day 5 (SV5) and from day 6 to weaning (SVW), respectively. The estimates of maternal heritability for SVB, SV5 and SVW were, respectively, 0.057, 0.040 and 0.030 in Landrace, and 0.050, 0.038 and 0.019 in Yorkshire. Both direct and maternal genetic correlations between the three survival traits were low and not significantly different from zero, except for a moderate direct genetic correlation between SVB and SV5 and between SV5 and SVW in Landrace. Direct and maternal genetic correlations between piglet birth weight (BW) and SV5 were moderately high, but the correlations between BW and SVB and between BW and SVW were low and most of them were not significantly different from zero. These results suggest that effective genetic improvement in piglet survival before weaning by selection should be based on both direct and maternal additive genetic effects and treat survival in different periods as different traits.

  5. 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.

  6. 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...

  7. Pricing Volatility Derivatives Under the Modified Constant Elasticity of Variance Model

    OpenAIRE

    Leunglung Chan; Eckhard Platen

    2015-01-01

    This paper studies volatility derivatives such as variance and volatility swaps, options on variance in the modified constant elasticity of variance model using the benchmark approach. The analytical expressions of pricing formulas for variance swaps are presented. In addition, the numerical solutions for variance swaps, volatility swaps and options on variance are demonstrated.

  8. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

    2008-01-01

    In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...

  9. Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance.

    Science.gov (United States)

    Hickey, John M; Veerkamp, Roel F; Calus, Mario P L; Mulder, Han A; Thompson, Robin

    2009-02-09

    Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values.

  10. minimum variance estimation of yield parameters of rubber tree with ...

    African Journals Online (AJOL)

    2013-03-01

    Mar 1, 2013 ... STAMP, an OxMetric modular software system for time series analysis, was used to estimate the yield ... derlying regression techniques. .... Kalman Filter Minimum Variance Estimation of Rubber Tree Yield Parameters. 83.

  11. Detecting Pulsars with Interstellar Scintillation in Variance Images

    CERN Document Server

    Dai, S; Bell, M E; Coles, W A; Hobbs, G; Ekers, R D; Lenc, E

    2016-01-01

    Pulsars are the only cosmic radio sources known to be sufficiently compact to show diffractive interstellar scintillations. Images of the variance of radio signals in both time and frequency can be used to detect pulsars in large-scale continuum surveys using the next generation of synthesis radio telescopes. This technique allows a search over the full field of view while avoiding the need for expensive pixel-by-pixel high time resolution searches. We investigate the sensitivity of detecting pulsars in variance images. We show that variance images are most sensitive to pulsars whose scintillation time-scales and bandwidths are close to the subintegration time and channel bandwidth. Therefore, in order to maximise the detection of pulsars for a given radio continuum survey, it is essential to retain a high time and frequency resolution, allowing us to make variance images sensitive to pulsars with different scintillation properties. We demonstrate the technique with Murchision Widefield Array data and show th...

  12. 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.

  13. 40 CFR 141.4 - Variances and exemptions.

    Science.gov (United States)

    2010-07-01

    ... Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions. (a... maintenance of the distribution system. ...

  14. Fundamental Indexes As Proxies For Mean-Variance Efficient Portfolios

    National Research Council Canada - National Science Library

    Kathleen Hodnett; Gearé Botes; Khumbudzo Daswa; Kimberly Davids; Emmanuel Che Fongwa; Candice Fortuin

    2014-01-01

      Mean-variance efficiency was first explained by Markowitz (1952) who derived an efficient frontier comprised of portfolios with the highest expected returns for a given level of risk borne by the investor...

  15. TESTS FOR VARIANCE COMPONENTS IN VARYING COEFFICIENT MIXED MODELS

    National Research Council Canada - National Science Library

    Zaixing Li; Yuedong Wang; Ping Wu; Wangli Xu; Lixing Zhu

    2012-01-01

    .... To address the question of whether a varying coefficient mixed model can be reduced to a simpler varying coefficient model, we develop one-sided tests for the null hypothesis that all the variance components are zero...

  16. Estimating the generalized concordance correlation coefficient through variance components.

    Science.gov (United States)

    Carrasco, Josep L; Jover, Lluís

    2003-12-01

    The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.

  17. Variance estimation in neutron coincidence counting using the bootstrap method

    Energy Technology Data Exchange (ETDEWEB)

    Dubi, C., E-mail: chendb331@gmail.com [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Ocherashvilli, A.; Ettegui, H. [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Pedersen, B. [Nuclear Security Unit, Institute for Transuranium Elements, Via E. Fermi, 2749 JRC, Ispra (Italy)

    2015-09-11

    In the study, we demonstrate the implementation of the “bootstrap” method for a reliable estimation of the statistical error in Neutron Multiplicity Counting (NMC) on plutonium samples. The “bootstrap” method estimates the variance of a measurement through a re-sampling process, in which a large number of pseudo-samples are generated, from which the so-called bootstrap distribution is generated. The outline of the present study is to give a full description of the bootstrapping procedure, and to validate, through experimental results, the reliability of the estimated variance. Results indicate both a very good agreement between the measured variance and the variance obtained through the bootstrap method, and a robustness of the method with respect to the duration of the measurement and the bootstrap parameters.

  18. Dimension free and infinite variance tail estimates on Poisson space

    OpenAIRE

    Breton, J. C.; Houdré, C.; Privault, N.

    2004-01-01

    Concentration inequalities are obtained on Poisson space, for random functionals with finite or infinite variance. In particular, dimension free tail estimates and exponential integrability results are given for the Euclidean norm of vectors of independent functionals. In the finite variance case these results are applied to infinitely divisible random variables such as quadratic Wiener functionals, including L\\'evy's stochastic area and the square norm of Brownian paths. In the infinite vari...

  19. 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 +

  20. Wavelet Variance Analysis of EEG Based on Window Function

    Institute of Scientific and Technical Information of China (English)

    ZHENG Yuan-zhuang; YOU Rong-yi

    2014-01-01

    A new wavelet variance analysis method based on window function is proposed to investigate the dynamical features of electroencephalogram (EEG).The ex-prienmental results show that the wavelet energy of epileptic EEGs are more discrete than normal EEGs, and the variation of wavelet variance is different between epileptic and normal EEGs with the increase of time-window width. Furthermore, it is found that the wavelet subband entropy (WSE) of the epileptic EEGs are lower than the normal EEGs.

  1. 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 ...

  2. Multiperiod mean-variance efficient portfolios with endogenous liabilities

    OpenAIRE

    Markus LEIPPOLD; Trojani, Fabio; Vanini, Paolo

    2011-01-01

    We study the optimal policies and mean-variance frontiers (MVF) of a multiperiod mean-variance optimization of assets and liabilities (AL). This makes the analysis more challenging than for a setting based on purely exogenous liabilities, in which the optimization is only performed on the assets while keeping liabilities fixed. We show that, under general conditions for the joint AL dynamics, the optimal policies and the MVF can be decomposed into an orthogonal set of basis returns using exte...

  3. 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 ...

  4. Estimating Income Variances by Probability Sampling: A Case Study

    Directory of Open Access Journals (Sweden)

    Akbar Ali Shah

    2010-08-01

    Full Text Available The main focus of the study is to estimate variability in income distribution of households by conducting a survey. The variances in income distribution have been calculated by probability sampling techniques. The variances are compared and relative gains are also obtained. It is concluded that the income distribution has been better as compared to first Household Income and Expenditure Survey (HIES conducted in Pakistan 1993-94.

  5. Testing for Causality in Variance Usinf Multivariate GARCH Models

    OpenAIRE

    Christian M. Hafner; Herwartz, Helmut

    2008-01-01

    Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently, little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causality in var...

  6. Testing for causality in variance using multivariate GARCH models

    OpenAIRE

    Hafner, Christian; Herwartz, H.

    2004-01-01

    textabstractTests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causa...

  7. 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.

  8. Variance estimation for systematic designs in spatial surveys.

    Science.gov (United States)

    Fewster, R M

    2011-12-01

    In spatial surveys for estimating the density of objects in a survey region, systematic designs will generally yield lower variance than random designs. However, estimating the systematic variance is well known to be a difficult problem. Existing methods tend to overestimate the variance, so although the variance is genuinely reduced, it is over-reported, and the gain from the more efficient design is lost. The current approaches to estimating a systematic variance for spatial surveys are to approximate the systematic design by a random design, or approximate it by a stratified design. Previous work has shown that approximation by a random design can perform very poorly, while approximation by a stratified design is an improvement but can still be severely biased in some situations. We develop a new estimator based on modeling the encounter process over space. The new "striplet" estimator has negligible bias and excellent precision in a wide range of simulation scenarios, including strip-sampling, distance-sampling, and quadrat-sampling surveys, and including populations that are highly trended or have strong aggregation of objects. We apply the new estimator to survey data for the spotted hyena (Crocuta crocuta) in the Serengeti National Park, Tanzania, and find that the reported coefficient of variation for estimated density is 20% using approximation by a random design, 17% using approximation by a stratified design, and 11% using the new striplet estimator. This large reduction in reported variance is verified by simulation. © 2011, The International Biometric Society.

  9. Analytic variance estimates of Swank and Fano factors.

    Science.gov (United States)

    Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank

    2014-07-01

    Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.

  10. 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.

  11. Analytic variance estimates of Swank and Fano factors

    Energy Technology Data Exchange (ETDEWEB)

    Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov [US Food and Drug Administration, Silver Spring, Maryland 20993 (United States)

    2014-07-15

    Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.

  12. APLICAÇÃO DA METODOLOGIA DE MODELOS MISTOS (REML/BLUP NA ESTIMAÇÃO DE COMPONENTES DE VARIÂNCIA E PREDIÇÃO DE VALORES GENÉTICOS EM PUPUNHEIRA (Bactris gasipaes APLICATION OF THE MIXED MODEL METHODOLOGY (REML/BLUP IN VARIANCE COMPONENTS ESTIMATION AND PREDICTION OF GENETIC VALUES IN PEACH PALM (Bactris gasipaes

    Directory of Open Access Journals (Sweden)

    JOÃO TOMÉ DE FARIAS NETO

    2001-08-01

    ,70%, PRB (6,15%. Os ganhos genéticos preditos em relação à média da população para PP foram de 7,18% na situação de LP e 8,40% para CP, com tamanho efetivo de 30,38 e 19,00, respectivamente.The peach palm is a very useful plant for feeding Brazilians as fruit or palm heart producer. The interest for the peach palm besides being a perennial culture is: growth in full sun, precocity, rusticity, capacity to shoot, flavor and non-darkening of the palm heart after the cut. Estimates of genetic parameters in peach palm are scarce and constitute the most important tool to guide the improvement programs. The objective of this work was to study the genetic variability and estimate the individual genetic value as selection criterion, using the BLUP/REML procedure (Best linear unbiased prediction/restricted maximum likelihood. Two selection strategies for the palm heart production trait were adopted: a short term (CP - selection of the 9 families with 31 individuals of bigger genetic value and a long term (LP - selection of the 15 families with 53 individuals. The progenies were evaluated in randomized block design with three replications, the plots were composed by rows of five plants, spaced in 2.0 m x 1.0 m and with a row around the experiment in the Experimental Field of Matapi, Porto Grande municipality, Amapa State, Brazil. The evaluation was accomplished to the 26 months after planting (2nd evaluation being collected data of plant height (AP, diameter of the plant to the lap height (DPC, palm heart size (TP, palm heart diameter (DP, residual apical weight (PRA, basal weight (PRB and of the liquid palm heart (PP (exportation type. The data of AP, DPC, TP and DP corresponded to the clump of roots averages that presented more than a stem. However for the characters PA, PRB and PP corresponded the sum of the stems in the clump of roots. In general, the population presented low genetic variability. The narrow sense heritability at the individuals level was: AP (18.44%, DPC

  13. 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.

  14. The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

    DEFF Research Database (Denmark)

    Bilde, T.; Friberg, U.; Maklakov, A.A.

    2008-01-01

    Background Quantifying the amount of standing genetic variation in fitness represents an empirical challenge. Unfortunately, the shortage of detailed studies of the genetic architecture of fitness has hampered progress in several domains of evolutionary biology. One such area is the study of sexual...... variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects. Conclusion Our results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should...... is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis) for F1 productivity. We discuss the processes that may maintain additive and non-additive genetic variance for fitness and how these relate to indirect selection...

  15. 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).

  16. Variance-based fingerprint distance adjustment algorithm for indoor localization

    Institute of Scientific and Technical Information of China (English)

    Xiaolong Xu; Yu Tang; Xinheng Wang; Yun Zhang

    2015-01-01

    The multipath effect and movements of people in in-door environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength in-dication (RSSI) and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm (VFDA). Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to im-prove its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in in-door environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.

  17. Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions

    Science.gov (United States)

    Luhar, Ashok K.

    2010-05-01

    Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.

  18. Application of variance components estimation to calibrate geoid error models.

    Science.gov (United States)

    Guo, Dong-Mei; Xu, Hou-Ze

    2015-01-01

    The method of using Global Positioning System-leveling data to obtain orthometric heights has been well studied. A simple formulation for the weighted least squares problem has been presented in an earlier work. This formulation allows one directly employing the errors-in-variables models which completely descript the covariance matrices of the observables. However, an important question that what accuracy level can be achieved has not yet to be satisfactorily solved by this traditional formulation. One of the main reasons for this is the incorrectness of the stochastic models in the adjustment, which in turn allows improving the stochastic models of measurement noises. Therefore the issue of determining the stochastic modeling of observables in the combined adjustment with heterogeneous height types will be a main focus point in this paper. Firstly, the well-known method of variance component estimation is employed to calibrate the errors of heterogeneous height data in a combined least square adjustment of ellipsoidal, orthometric and gravimetric geoid. Specifically, the iterative algorithms of minimum norm quadratic unbiased estimation are used to estimate the variance components for each of heterogeneous observations. Secondly, two different statistical models are presented to illustrate the theory. The first method directly uses the errors-in-variables as a priori covariance matrices and the second method analyzes the biases of variance components and then proposes bias-corrected variance component estimators. Several numerical test results show the capability and effectiveness of the variance components estimation procedure in combined adjustment for calibrating geoid error model.

  19. Componentes de (covariância e parâmetros genéticos de caracteres pós-desmama em bovinos da raça Angus (Co variance components and genetic parameters of post-weaning traits in Angus cattle

    Directory of Open Access Journals (Sweden)

    Fernando Flores Cardoso

    2004-04-01

    Full Text Available Foram determinados os componentes de (covariância para caracteres do período pós-desmama na raça Angus e de covariância com peso ao nascer (PN e caracteres do período pré-desmama por intermédio de um modelo animal. Utilizaram-se dados de 18.921 animais com registros de peso à desmama e ao sobreano, dos quais 4.452 tinham avaliações completas para escores visuais à desmama e ao sobreano. Registros de PN estavam disponíveis para 11.788 animais. As herdabilidades do ganho de peso pós-desmama (GP205 e dos escores de conformação (CS, precocidade (GS, musculatura (MS e tamanho (TS ao sobreano foram de 0,20, 0,19, 0,25, 0,26 e 0,24 respectivamente. As correlações genéticas entre os caracteres estudados foram todas positivas: entre GP205 e escores visuais variaram de 0,50 a 0,71; para os escores ao sobreano entre si, de 0,22 a 0,94; entre GP205 e PN foram de 0,14; entre GP205 e ganho pré-desmama, de 0,23; e para o mesmo escore visual observado à desmama e ao sobreano, de 0,90 a 0,99. Esses resultados indicam que é possível selecionar para GP205, sem aumento importante do PN, e que a seleção para GP205 deverá promover uma mudança genética correlacionada em escores visuais ao sobreano.(Covariance components were determined for post-weaning traits, and covariances with birth weight (BW and pre-weaning traits, in Angus cattle using an animal model. Records of weaning and yearling weights of 18,921 animals were used and from these 4,452 had complete evaluations of visual scores at weaning and post-weaning phases. Records of BW were available for 11,788 animals. Heritabilities of post-weaning gain (GP205 and visual scores for conformation (YC, precocity (YP, muscling (YM and size (YS were 0.20, 0.19, 0.25, 0.26 and 0.24, respectively. Genetic correlations among all traits considered were positive: between GP205 and visual scores the range was from 0.50 to 0.71; for yearling scores among themselves from 0.22 to 0.94; between GP205

  20. On testing an unspecified function through a linear mixed effects model with multiple variance components.

    Science.gov (United States)

    Wang, Yuanjia; Chen, Huaihou

    2012-12-01

    We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 10(8) simulations) and asymptotic approximation may be unreliable and conservative. © 2012, The International Biometric Society.

  1. Estimation of additive and dominance variance for reproductive traits from different models in Duroc purebred

    Directory of Open Access Journals (Sweden)

    Talerngsak Angkuraseranee

    2010-05-01

    Full Text Available The additive and dominance genetic variances of 5,801 Duroc reproductive and growth records were estimated usingBULPF90 PC-PACK. Estimates were obtained for number born alive (NBA, birth weight (BW, number weaned (NW, andweaning weight (WW. Data were analyzed using two mixed model equations. The first model included fixed effects andrandom effects identifying inbreeding depression, additive gene effect and permanent environments effects. The secondmodel was similar to the first model, but included the dominance genotypic effect. Heritability estimates of NBA, BW, NWand WW from the two models were 0.1558/0.1716, 0.1616/0.1737, 0.0372/0.0874 and 0.1584/0.1516 respectively. Proportionsof dominance effect to total phenotypic variance from the dominance model were 0.1024, 0.1625, 0.0470, and 0.1536 for NBA,BW, NW and WW respectively. Dominance effects were found to have sizable influence on the litter size traits analyzed.Therefore, genetic evaluation with the dominance model (Model 2 is found more appropriate than the animal model (Model 1.

  2. Direct and maternal (co)variance components and heritability estimates for body weights in Chokla sheep.

    Science.gov (United States)

    Kushwaha, B P; Mandal, A; Arora, A L; Kumar, R; Kumar, S; Notter, D R

    2009-08-01

    Estimates of (co)variance components were obtained for weights at birth, weaning and 6, 9 and 12 months of age in Chokla sheep maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, over a period of 21 years (1980-2000). Records of 2030 lambs descended from 150 rams and 616 ewes were used in the study. Analyses were carried out by restricted maximum likelihood (REML) fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits. The best model was chosen after testing the improvement of the log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Heritability estimates for weight at birth, weaning and 6, 9 and 12 months of age were 0.20, 0.18, 0.16, 0.22 and 0.23, respectively in the best models. Additive maternal and maternal permanent environmental effects were both significant at birth, accounting for 9% and 12% of phenotypic variance, respectively, but the source of maternal effects (additive versus permanent environmental) at later ages could not be clearly identified. The estimated repeatabilities across years of ewe effects on lamb body weights were 0.26, 0.14, 0.12, 0.13, and 0.15 at birth, weaning, 6, 9 and 12 months of age, respectively. These results indicate that modest rates of genetic progress are possible for all weights.

  3. Longitudinal Analysis of Residual Feed Intake in Mink using Random Regression with Heterogeneous Residual Variance

    DEFF Research Database (Denmark)

    Shirali, Mahmoud; Nielsen, Vivi Hunnicke; Møller, Steen Henrik

    Heritability of residual feed intake (RFI) increased from low to high over the growing period in male and female mink. The lowest heritability for RFI (male: 0.04 ± 0.01 standard deviation (SD); female: 0.05 ± 0.01 SD) was in early and the highest heritability (male: 0.33 ± 0.02; female: 0.34 ± 0...... at the end compared to the early growing period suggesting that heterogeneous residual variance should be considered for analyzing feed efficiency data in mink. This study suggests random regression methods are suitable for analyzing feed efficiency and that genetic selection for RFI in mink is promising........02 SD) was achieved at the late growth stages. The genetic correlation between different growth stages for RFI showed a high association (0.91 to 0.98) between early and late growing periods. However, phenotypic correlations were lower from 0.29 to 0.50. The residual variances were substantially higher...

  4. Sensitivity to Estimation Errors in Mean-variance Models

    Institute of Scientific and Technical Information of China (English)

    Zhi-ping Chen; Cai-e Zhao

    2003-01-01

    In order to give a complete and accurate description about the sensitivity of efficient portfolios to changes in assets' expected returns, variances and covariances, the joint effect of estimation errors in means, variances and covariances on the efficient portfolio's weights is investigated in this paper. It is proved that the efficient portfolio's composition is a Lipschitz continuous, differentiable mapping of these parameters under suitable conditions. The change rate of the efficient portfolio's weights with respect to variations about riskreturn estimations is derived by estimating the Lipschitz constant. Our general quantitative results show thatthe efficient portfolio's weights are normally not so sensitive to estimation errors about means and variances .Moreover, we point out those extreme cases which might cause stability problems and how to avoid them in practice. Preliminary numerical results are also provided as an illustration to our theoretical results.

  5. Expectation Values and Variance Based on Lp-Norms

    Directory of Open Access Journals (Sweden)

    George Livadiotis

    2012-11-01

    Full Text Available This analysis introduces a generalization of the basic statistical concepts of expectation values and variance for non-Euclidean metrics induced by Lp-norms. The non-Euclidean Lp means are defined by exploiting the fundamental property of minimizing the Lp deviations that compose the Lp variance. These Lp expectation values embody a generic formal scheme of means characterization. Having the p-norm as a free parameter, both the Lp-normed expectation values and their variance are flexible to analyze new phenomena that cannot be described under the notions of classical statistics based on Euclidean norms. The new statistical approach provides insights into regression theory and Statistical Physics. Several illuminating examples are examined.

  6. CMB-S4 and the Hemispherical Variance Anomaly

    CERN Document Server

    O'Dwyer, Marcio; Knox, Lloyd; Starkman, Glenn D

    2016-01-01

    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. In this context, the northern hemisphere displays an anomalously low variance while the southern hemisphere appears unremarkable (consistent with expectations from the best-fitting theory, $\\Lambda$CDM). 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 ba...

  7. 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...... is not the full input space. Hence, when applying the model to future data the model is effectively blind to the missed orthogonal subspace. This can lead to an inflated variance of hidden variables estimated in the training set and when the model is applied to test data we may find that the hidden variables...... 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...

  8. 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...... constraint. Our approach, only requiring option implied volatilities and daily returns for the underlying, provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents' expectations under extreme market conditions....... 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....

  9. Saturation of number variance in embedded random-matrix ensembles.

    Science.gov (United States)

    Prakash, Ravi; Pandey, Akhilesh

    2016-05-01

    We study fluctuation properties of embedded random matrix ensembles of noninteracting particles. For ensemble of two noninteracting particle systems, we find that unlike the spectra of classical random matrices, correlation functions are nonstationary. In the locally stationary region of spectra, we study the number variance and the spacing distributions. The spacing distributions follow the Poisson statistics, which is a key behavior of uncorrelated spectra. The number variance varies linearly as in the Poisson case for short correlation lengths but a kind of regularization occurs for large correlation lengths, and the number variance approaches saturation values. These results are known in the study of integrable systems but are being demonstrated for the first time in random matrix theory. We conjecture that the interacting particle cases, which exhibit the characteristics of classical random matrices for short correlation lengths, will also show saturation effects for large correlation lengths.

  10. The positioning algorithm based on feature variance of billet character

    Science.gov (United States)

    Yi, Jiansong; Hong, Hanyu; Shi, Yu; Chen, Hongyang

    2015-12-01

    In the process of steel billets recognition on the production line, the key problem is how to determine the position of the billet from complex scenes. To solve this problem, this paper presents a positioning algorithm based on the feature variance of billet character. Using the largest intra-cluster variance recursive method based on multilevel filtering, the billet characters are segmented completely from the complex scenes. There are three rows of characters on each steel billet, we are able to determine whether the connected regions, which satisfy the condition of the feature variance, are on a straight line. Then we can accurately locate the steel billet. The experimental results demonstrated that the proposed method in this paper is competitive to other methods in positioning the characters and it also reduce the running time. The algorithm can provide a better basis for the character recognition.

  11. Saturation of number variance in embedded random-matrix ensembles

    Science.gov (United States)

    Prakash, Ravi; Pandey, Akhilesh

    2016-05-01

    We study fluctuation properties of embedded random matrix ensembles of noninteracting particles. For ensemble of two noninteracting particle systems, we find that unlike the spectra of classical random matrices, correlation functions are nonstationary. In the locally stationary region of spectra, we study the number variance and the spacing distributions. The spacing distributions follow the Poisson statistics, which is a key behavior of uncorrelated spectra. The number variance varies linearly as in the Poisson case for short correlation lengths but a kind of regularization occurs for large correlation lengths, and the number variance approaches saturation values. These results are known in the study of integrable systems but are being demonstrated for the first time in random matrix theory. We conjecture that the interacting particle cases, which exhibit the characteristics of classical random matrices for short correlation lengths, will also show saturation effects for large correlation lengths.

  12. 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.

  13. Recursive identification for multidimensional ARMA processes with increasing variances

    Institute of Scientific and Technical Information of China (English)

    CHEN Hanfu

    2005-01-01

    In time series analysis, almost all existing results are derived for the case where the driven noise {wn} in the MA part is with bounded variance (or conditional variance). In contrast to this, the paper discusses how to identify coefficients in a multidimensional ARMA process with fixed orders, but in its MA part the conditional moment E(‖wn‖β| Fn-1), β> 2 Is possible to grow up at a rate of a power of logn. The wellknown stochastic gradient (SG) algorithm is applied to estimating the matrix coefficients of the ARMA process, and the reasonable conditions are given to guarantee the estimate to be strongly consistent.

  14. 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

  15. 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....

  16. Precise Asymptotics of Error Variance Estimator in Partially Linear Models

    Institute of Scientific and Technical Information of China (English)

    Shao-jun Guo; Min Chen; Feng Liu

    2008-01-01

    In this paper, we focus our attention on the precise asymptoties of error variance estimator in partially linear regression models, yi = xTi β + g(ti) +εi, 1 ≤i≤n, {εi,i = 1,... ,n } are i.i.d random errors with mean 0 and positive finite variance q2. Following the ideas of Allan Gut and Aurel Spataru[7,8] and Zhang[21],on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.

  17. Least-squares variance component estimation: theory and GPS applications

    OpenAIRE

    Amiri-Simkooei, A.

    2007-01-01

    In this thesis we study the method of least-squares variance component estimation (LS-VCE) and elaborate on theoretical and practical aspects of the method. We show that LS-VCE is a simple, flexible, and attractive VCE-method. The LS-VCE method is simple because it is based on the well-known principle of least-squares. With this method the estimation of the (co)variance components is based on a linear model of observation equations. The method is flexible since it works with a user-defined we...

  18. The dynamic Allan Variance IV: characterization of atomic clock anomalies.

    Science.gov (United States)

    Galleani, Lorenzo; Tavella, Patrizia

    2015-05-01

    The number of applications where precise clocks play a key role is steadily increasing, satellite navigation being the main example. Precise clock anomalies are hence critical events, and their characterization is a fundamental problem. When an anomaly occurs, the clock stability changes with time, and this variation can be characterized with the dynamic Allan variance (DAVAR). We obtain the DAVAR for a series of common clock anomalies, namely, a sinusoidal term, a phase jump, a frequency jump, and a sudden change in the clock noise variance. These anomalies are particularly common in space clocks. Our analytic results clarify how the clock stability changes during these anomalies.

  19. On Variance and Covariance for Bounded Linear Operators

    Institute of Scientific and Technical Information of China (English)

    Chia Shiang LIN

    2001-01-01

    In this paper we initiate a study of covariance and variance for two operators on a Hilbert space, proving that the c-v (covariance-variance) inequality holds, which is equivalent to the CauchySchwarz inequality. As for applications of the c-v inequality we prove uniformly the Bernstein-type incqualities and equalities, and show the generalized Heinz-Kato-Furuta-type inequalities and equalities,from which a generalization and sharpening of Reid's inequality is obtained. We show that every operator can be expressed as a p-hyponormal-type, and a hyponornal-type operator. Finally, some new characterizations of the Furuta inequality are given.

  20. WHY SCHIZOPHRENIA GENETICS NEEDS EPIGENETICS: A REVIEW

    OpenAIRE

    Maric, Nadja; Svrakic, Dragan

    2012-01-01

    Schizophrenia (SZ) is a highly heritable disorder, with about 80% of the variance attributable to genetic factors. There is accumulating evidence that both common genetic variants with small effects and rare genetic lesions with large effects determine risk of SZ. As recently shown, thousands of common single nucleotide polymorphisms (SNPs), each with small effect, cumulatively could explain about 30% of the underlying genetic risk of SZ. On the other hand, rare and large copy number...

  1. Efeitos da Correção de Dados na Redução da Heterogeneidade das Variâncias Genética, Ambiental e Fenotípica em Testes de Progênies de Eucalyptus grandis W. Hill ex Maiden Effects of Different Data Transformation Methods on the Reduction of the Genetic, Environmental and Phenotypic Variance in the Progeny Trial of Eucalyptus grandis W. Hill ex Maiden

    Directory of Open Access Journals (Sweden)

    José Elidney Pinto Júnior

    2011-03-01

    recursos. A variabilidade genética presente foi representada pelos valores moderados obtidos de herdabilidade individual, no sentido restrito, para o crescimento em diâmetro à altura do peito (DAP, nos três locais estudados. A adoção de estratégias e critérios propostos à seleção permitirá compor uma População Selecionada com duzentos indivíduos de maiores valores genéticos, com número efetivo de progênies adequado, propiciando ganhos para DAP entre 12,89% a 24,33%, em relação à média experimental, no estabelecimento de um Pomar de Sementes por Mudas. A seleção dos vinte indivíduos com os maiores valores genéticos aditivos, para o estabelecimento de um Pomar Clonal de Sementes, poderá propiciar ganhos para DAP entre 17,18% e 50,95%, em relação à média experimental. Por sua vez, a seleção dos vinte melhores indivíduos, com os maiores valores genotípicos, para o estabelecimento de um Jardim Clonal, poderá propiciar ganhos para DAP entre 22,40% a 82,16%, em relação à média experimental, para as plantações clonais resultantes do material selecionado em questão. 

This research work was developed in order to evaluate progeny trials of Eucalyptus grandis W. Hill ex Maiden using the software SELEGEN-REML/BLUP. The best trees were identified in order to be used in seedling and clonal orchards. Fifty three half-sib progenies of three Australian provenances were tested in the municipalities of Mogi Guaçu, Boa Esperança do Sul and Caçapava, all located in the State of São Paulo. A compacted families block experimental design was used with variable number of replicates, linear plots of six trees each, and a 3.00 x 2.00 m spacing. Two methods of data standardization or transformation were used in order to evaluate their efficiency in the reduction of the genetic, environmental and phenotypic variances. The transformation or  orrection of the data, performed with the ratio (hi/him between the square root of

  • 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 si

  • Analysis of Variance: What Is Your Statistical Software Actually Doing?

    Science.gov (United States)

    Li, Jian; Lomax, Richard G.

    2011-01-01

    Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…

  • Gender variance in Asia: discursive contestations and legal implications

    NARCIS (Netherlands)

    Wieringa, S.E.

    2010-01-01

    A recent court case in Indonesia in which a person diagnosed with an intersex condition was classified as a transsexual gives rise to a reflection on three discourses in which gender variance is discussed: the biomedical, the cultural, and the human rights discourse. This article discusses the

  • Permutation tests for multi-factorial analysis of variance

    NARCIS (Netherlands)

    Anderson, M.J.; Braak, ter C.J.F.

    2003-01-01

    Several permutation strategies are often possible for tests of individual terms in analysis-of-variance (ANOVA) designs. These include restricted permutations, permutation of whole groups of units, permutation of some form of residuals or some combination of these. It is unclear, especially for

  • A Hold-out method to correct PCA variance inflation

    DEFF Research Database (Denmark)

    Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Hansen, Lars Kai

    2012-01-01

    In this paper we analyze the problem of variance inflation experienced by the PCA algorithm when working in an ill-posed scenario where the dimensionality of the training set is larger than its sample size. In an earlier article a correction method based on a Leave-One-Out (LOO) procedure was int...

  • Similarities Derived from 3-D Nonlinear Psychophysics: Variance Distributions.

    Science.gov (United States)

    Gregson, Robert A. M.

    1994-01-01

    The derivation of the variance of similarity judgments is made from the 3-D process in nonlinear psychophysics. The idea of separability of dimensions in metric space theories of similarity is replaced by one parameter that represents the degree of a form of interdimensional cross-sampling. (SLD)

  • Infinite variance in fermion quantum Monte Carlo calculations.

    Science.gov (United States)

    Shi, Hao; Zhang, Shiwei

    2016-03-01

    For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

  • 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

  • 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

  • 20 CFR 901.40 - Proof; variance; amendment of pleadings.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Proof; variance; amendment of pleadings. 901.40 Section 901.40 Employees' Benefits JOINT BOARD FOR THE ENROLLMENT OF ACTUARIES REGULATIONS GOVERNING THE PERFORMANCE OF ACTUARIAL SERVICES UNDER THE EMPLOYEE RETIREMENT INCOME SECURITY ACT OF...

  • 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...

  • 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...... velocity component....

  • Estimation of dominance variance in purebred Yorkshire swine.

    Science.gov (United States)

    Culbertson, M S; Mabry, J W; Misztal, I; Gengler, N; Bertrand, J K; Varona, L

    1998-02-01

    We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11.

  • Common Persistence and Error-Correction Mode in Conditional Variance

    Institute of Scientific and Technical Information of China (English)

    LI Han-dong; ZHANG Shi-ying

    2001-01-01

    We firstly define the persistence and common persistence of vector GARCH process from the point of view of the integration, and then discuss the sufficient and necessary condition of the copersistence in variance. In the end of this paper, we give the properties and the error correction model of vector GARCH process under the condition of the co-persistence.

  • Bounds for Tail Probabilities of the Sample Variance

    Directory of Open Access Journals (Sweden)

    V. Bentkus

    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.

  • Variance Ranklets : Orientation-selective rank features for contrast modulations

    NARCIS (Netherlands)

    Azzopardi, George; Smeraldi, Fabrizio

    2009-01-01

    We introduce a novel type of orientation–selective rank features that are sensitive to contrast modulations (second–order stimuli). Variance Ranklets are designed in close analogy with the standard Ranklets, but use the Siegel–Tukey statistics for dispersion instead of the Wilcoxon statistics. Their

  • 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.

  • 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 s

  • Average local values and local variances in quantum mechanics

    CERN Document Server

    Muga, J G; Sala, P R

    1998-01-01

    Several definitions for the average local value and local variance of a quantum observable are examined and compared with their classical counterparts. An explicit way to construct an infinite number of these quantities is provided. It is found that different classical conditions may be satisfied by different definitions, but none of the quantum definitions examined is entirely consistent with all classical requirements.

    1. Hedging with stock index futures: downside risk versus the variance

      NARCIS (Netherlands)

      Brouwer, F.; Nat, van der M.

      1995-01-01

      In this paper we investigate hedging a stock portfolio with stock index futures.Instead of defining the hedge ratio as the minimum variance hedge ratio, we considerseveral measures of downside risk: the semivariance according to Markowitz [ 19591 andthe various lower partial moments according to Fis

    2. Least-squares variance component estimation: theory and GPS applications

      NARCIS (Netherlands)

      Amiri-Simkooei, A.

      2007-01-01

      In this thesis we study the method of least-squares variance component estimation (LS-VCE) and elaborate on theoretical and practical aspects of the method. We show that LS-VCE is a simple, flexible, and attractive VCE-method. The LS-VCE method is simple because it is based on the well-known

    3. 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...

    4. Multivariate variance targeting in the BEKK-GARCH model

      DEFF Research Database (Denmark)

      Pedersen, Rasmus S.; Rahbæk, 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...

    5. A comparison between temporal and subband minimum variance adaptive beamforming

      DEFF Research Database (Denmark)

      Diamantis, Konstantinos; Voxen, Iben Holfort; Greenaway, Alan H.

      2014-01-01

      This paper compares the performance between temporal and subband Minimum Variance (MV) beamformers for medical ultrasound imaging. Both adaptive methods provide an optimized set of apodization weights but are implemented in the time and frequency domains respectively. Their performance is evaluated...

    6. CAIXA. II. AGNs from excess variance analysis (Ponti+, 2012) [Dataset

      NARCIS (Netherlands)

      Ponti, G.; Papadakis, I.E.; Bianchi, S.; Guainazzi, M.; Matt, G.; Uttley, P.; Bonilla, N.F.

      2012-01-01

      We report on the results of the first XMM-Newton systematic "excess variance" study of all the radio quiet, X-ray unobscured AGN. The entire sample consist of 161 sources observed by XMM-Newton for more than 10ks in pointed observations, which is the largest sample used so far to study AGN X-ray var

    7. Gender variance in Asia: discursive contestations and legal implications

      NARCIS (Netherlands)

      Wieringa, S.E.

      2010-01-01

      A recent court case in Indonesia in which a person diagnosed with an intersex condition was classified as a transsexual gives rise to a reflection on three discourses in which gender variance is discussed: the biomedical, the cultural, and the human rights discourse. This article discusses the impli

    8. CAIXA. II. AGNs from excess variance analysis (Ponti+, 2012) [Dataset

      NARCIS (Netherlands)

      Ponti, G.; Papadakis, I.E.; Bianchi, S.; Guainazzi, M.; Matt, G.; Uttley, P.; Bonilla, N.F.

      2012-01-01

      We report on the results of the first XMM-Newton systematic "excess variance" study of all the radio quiet, X-ray unobscured AGN. The entire sample consist of 161 sources observed by XMM-Newton for more than 10ks in pointed observations, which is the largest sample used so far to study AGN X-ray var

    9. Infinite variance in fermion quantum Monte Carlo calculations

      Science.gov (United States)

      Shi, Hao; Zhang, Shiwei

      2016-03-01

      For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

    10. Testing for causality in variance using multivariate GARCH models

      NARCIS (Netherlands)

      C.M. Hafner (Christian); H. Herwartz

      2004-01-01

      textabstractTests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual

    11. Variance Components for NLS: Partitioning the Design Effect.

      Science.gov (United States)

      Folsom, Ralph E., Jr.

      This memorandum demonstrates a variance components methodology for partitioning the overall design effect (D) for a ratio mean into stratification (S), unequal weighting (W), and clustering (C) effects, so that D = WSC. In section 2, a sample selection scheme modeled after the National Longitudinal Study of the High School Class of 1972 (NKS)…

    12. 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.

    13. Simultaneous optimal estimates of fixed effects and variance components in the mixed model

      Institute of Scientific and Technical Information of China (English)

      WU Mixia; WANG Songgui

      2004-01-01

      For a general linear mixed model with two variance components, a set of simple conditions is obtained, under which, (i) the least squares estimate of the fixed effects and the analysis of variance (ANOVA) estimates of variance components are proved to be uniformly minimum variance unbiased estimates simultaneously; (ii) the exact confidence intervals of the fixed effects and uniformly optimal unbiased tests on variance components are given; (iii) the exact probability expression of ANOVA estimates of variance components taking negative value is obtained.

    14. Genetic landscapes GIS Toolbox: tools to map patterns of genetic divergence and diversity.

      Science.gov (United States)

      Vandergast, Amy G.; Perry, William M.; Lugo, Roberto V.; Hathaway, Stacie A.

      2011-01-01

      The Landscape Genetics GIS Toolbox contains tools that run in the Geographic Information System software, ArcGIS, to map genetic landscapes and to summarize multiple genetic landscapes as average and variance surfaces. These tools can be used to visualize the distribution of genetic diversity across geographic space and to study associations between patterns of genetic diversity and geographic features or other geo-referenced environmental data sets. Together, these tools create genetic landscape surfaces directly from tables containing genetic distance or diversity data and sample location coordinates, greatly reducing the complexity of building and analyzing these raster surfaces in a Geographic Information System.

    15. Convergence of Recursive Identification for ARMAX Process with Increasing Variances

      Institute of Scientific and Technical Information of China (English)

      JIN Ya; LUO Guiming

      2007-01-01

      The autoregressive moving average exogenous (ARMAX) model is commonly adopted for describing linear stochastic systems driven by colored noise. The model is a finite mixture with the ARMA component and external inputs. In this paper we focus on a paramete estimate of the ARMAX model. Classical modeling methods are usually based on the assumption that the driven noise in the moving average (MA) part has bounded variances, while in the model considered here the variances of noise may increase by a power of log n. The plant parameters are identified by the recursive stochastic gradient algorithm. The diminishing excitation technique and some results of martingale difference theory are adopted in order to prove the convergence of the identification. Finally, some simulations are given to show the theoretical results.

    16. 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.

    17. Climate variance influence on the non-stationary plankton dynamics.

      Science.gov (United States)

      Molinero, Juan Carlos; Reygondeau, Gabriel; Bonnet, Delphine

      2013-08-01

      We examined plankton responses to climate variance by using high temporal resolution data from 1988 to 2007 in the Western English Channel. Climate variability modified both the magnitude and length of the seasonal signal of sea surface temperature, as well as the timing and depth of the thermocline. These changes permeated the pelagic system yielding conspicuous modifications in the phenology of autotroph communities and zooplankton. The climate variance envelope, thus far little considered in climate-plankton studies, is closely coupled with the non-stationary dynamics of plankton, and sheds light on impending ecological shifts and plankton structural changes. Our study calls for the integration of the non-stationary relationship between climate and plankton in prognostic models on the productivity of marine ecosystems.

    18. 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 to these ......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...... to these two steps. Strong consistency is established under weak moment conditions, while sixth order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are indeed necessary....

    19. 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.

    20. Validation technique using mean and variance of kriging model

      Energy Technology Data Exchange (ETDEWEB)

      Kim, Ho Sung; Jung, Jae Jun; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of)

      2007-07-01

      To validate rigorously the accuracy of metamodel is an important research area in metamodel techniques. A leave-k-out cross-validation technique not only requires considerable computational cost but also cannot measure quantitatively the fidelity of metamodel. Recently, the average validation technique has been proposed. However the average validation criterion may stop a sampling process prematurely even if kriging model is inaccurate yet. In this research, we propose a new validation technique using an average and a variance of response during a sequential sampling method, such as maximum entropy sampling. The proposed validation technique becomes more efficient and accurate than cross-validation technique, because it integrates explicitly kriging model to achieve an accurate average and variance, rather than numerical integration. The proposed validation technique shows similar trend to root mean squared error such that it can be used as a strop criterion for sequential sampling.

    1. Explaining the Prevalence, Scaling and Variance of Urban Phenomena

      CERN Document Server

      Gomez-Lievano, Andres; Hausmann, Ricardo

      2016-01-01

      The prevalence of many urban phenomena changes systematically with population size. We propose a theory that unifies models of economic complexity and cultural evolution to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.

    2. 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.

    3. Sample variance and Lyman-alpha forest transmission statistics

      CERN Document Server

      Rollinde, Emmanuel; Schaye, Joop; Pâris, Isabelle; Petitjean, Patrick

      2012-01-01

      We compare the observed probability distribution function of the transmission in the \\HI\\ Lyman-alpha forest, measured from the UVES 'Large Programme' sample at redshifts z=[2,2.5,3], to results from the GIMIC cosmological simulations. Our measured values for the mean transmission and its PDF are in good agreement with published results. Errors on statistics measured from high-resolution data are typically estimated using bootstrap or jack-knife resampling techniques after splitting the spectra into chunks. We demonstrate that these methods tend to underestimate the sample variance unless the chunk size is much larger than is commonly the case. We therefore estimate the sample variance from the simulations. We conclude that observed and simulated transmission statistics are in good agreement, in particular, we do not require the temperature-density relation to be 'inverted'.

    4. Variance reduction methods applied to deep-penetration problems

      Energy Technology Data Exchange (ETDEWEB)

      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.

    5. Automated Extraction of Archaeological Traces by a Modified Variance Analysis

      Directory of Open Access Journals (Sweden)

      Tiziana D'Orazio

      2015-03-01

      Full Text Available This paper considers the problem of detecting archaeological traces in digital aerial images by analyzing the pixel variance over regions around selected points. In order to decide if a point belongs to an archaeological trace or not, its surrounding regions are considered. The one-way ANalysis Of VAriance (ANOVA is applied several times to detect the differences among these regions; in particular the expected shape of the mark to be detected is used in each region. Furthermore, an effect size parameter is defined by comparing the statistics of these regions with the statistics of the entire population in order to measure how strongly the trace is appreciable. Experiments on synthetic and real images demonstrate the effectiveness of the proposed approach with respect to some state-of-the-art methodologies.

    6. Variable variance Preisach model for multilayers with perpendicular magnetic anisotropy

      Science.gov (United States)

      Franco, A. F.; Gonzalez-Fuentes, C.; Morales, R.; Ross, C. A.; Dumas, R.; Åkerman, J.; Garcia, C.

      2016-08-01

      We present a variable variance Preisach model that fully accounts for the different magnetization processes of a multilayer structure with perpendicular magnetic anisotropy by adjusting the evolution of the interaction variance as the magnetization changes. We successfully compare in a quantitative manner the results obtained with this model to experimental hysteresis loops of several [CoFeB/Pd ] n multilayers. The effect of the number of repetitions and the thicknesses of the CoFeB and Pd layers on the magnetization reversal of the multilayer structure is studied, and it is found that many of the observed phenomena can be attributed to an increase of the magnetostatic interactions and subsequent decrease of the size of the magnetic domains. Increasing the CoFeB thickness leads to the disappearance of the perpendicular anisotropy, and such a minimum thickness of the Pd layer is necessary to achieve an out-of-plane magnetization.

    7. Analysis of variance in spectroscopic imaging data from human tissues.

      Science.gov (United States)

      Kwak, Jin Tae; Reddy, Rohith; Sinha, Saurabh; Bhargava, Rohit

      2012-01-17

      The analysis of cell types and disease using Fourier transform infrared (FT-IR) spectroscopic imaging is promising. The approach lacks an appreciation of the limits of performance for the technology, however, which limits both researcher efforts in improving the approach and acceptance by practitioners. One factor limiting performance is the variance in data arising from biological diversity, measurement noise or from other sources. Here we identify the sources of variation by first employing a high throughout sampling platform of tissue microarrays (TMAs) to record a sufficiently large and diverse set data. Next, a comprehensive set of analysis of variance (ANOVA) models is employed to analyze the data. Estimating the portions of explained variation, we quantify the primary sources of variation, find the most discriminating spectral metrics, and recognize the aspects of the technology to improve. The study provides a framework for the development of protocols for clinical translation and provides guidelines to design statistically valid studies in the spectroscopic analysis of tissue.

    8. The return of the variance: intraspecific variability in community ecology.

      Science.gov (United States)

      Violle, Cyrille; Enquist, Brian J; McGill, Brian J; Jiang, Lin; Albert, Cécile H; Hulshof, Catherine; Jung, Vincent; Messier, Julie

      2012-04-01

      Despite being recognized as a promoter of diversity and a condition for local coexistence decades ago, the importance of intraspecific variance has been neglected over time in community ecology. Recently, there has been a new emphasis on intraspecific variability. Indeed, recent developments in trait-based community ecology have underlined the need to integrate variation at both the intraspecific as well as interspecific level. We introduce new T-statistics ('T' for trait), based on the comparison of intraspecific and interspecific variances of functional traits across organizational levels, to operationally incorporate intraspecific variability into community ecology theory. We show that a focus on the distribution of traits at local and regional scales combined with original analytical tools can provide unique insights into the primary forces structuring communities.

    9. Genetic Discrimination

      Science.gov (United States)

      ... in Genetics Archive Regulation of Genetic Tests Genetic Discrimination Overview Many Americans fear that participating in research ... I) and employment (Title II). Read more Genetic Discrimination and Other Laws Genetic Discrimination and Other Laws ...

    10. Analysis of Variance in the Modern Design of Experiments

      Science.gov (United States)

      Deloach, Richard

      2010-01-01

      This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.

    11. Seasonal variance in P system models for metapopulations

      Institute of Scientific and Technical Information of China (English)

      Daniela Besozzi; Paolo Cazzaniga; Dario Pescini; Giancarlo Mauri

      2007-01-01

      Metapopulations are ecological models describing the interactions and the behavior of populations living in fragmented habitats. In this paper, metapopulations are modelled by means of dynamical probabilistic P systems, where additional structural features have been defined (e. g., a weighted graph associated with the membrane structure and the reduction of maximal parallelism). In particular, we investigate the influence of stochastic and periodic resource feeding processes, owing to seasonal variance, on emergent metapopulation dynamics.

    12. 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...... frequency derived in Bandi & Russell (2005a) and Bandi & Russell (2005b). For a realistic trading scenario, the efficiency gains resulting from our approach are in the range of 35% to 50%....

    13. VARIANCE OF NONLINEAR PHASE NOISE IN FIBER-OPTIC SYSTEM

      OpenAIRE

      RANJU KANWAR; SAMEKSHA BHASKAR

      2013-01-01

      In communication system, the noise process must be known, in order to compute the system performance. The nonlinear effects act as strong perturbation in long- haul system. This perturbation effects the signal, when interact with amplitude noise, and results in random motion of the phase of the signal. Based on the perturbation theory, the variance of nonlinear phase noise contaminated by both self- and cross-phase modulation, is derived analytically for phase-shift- keying system. Through th...

    14. Recombining binomial tree for constant elasticity of variance process

      OpenAIRE

      Hi Jun Choe; Jeong Ho Chu; So Jeong Shin

      2014-01-01

      The theme in this paper is the recombining binomial tree to price American put option when the underlying stock follows constant elasticity of variance(CEV) process. Recombining nodes of binomial tree are decided from finite difference scheme to emulate CEV process and the tree has a linear complexity. Also it is derived from the differential equation the asymptotic envelope of the boundary of tree. Conducting numerical experiments, we confirm the convergence and accuracy of the pricing by ou...

    15. PARAMETER-ESTIMATION FOR ARMA MODELS WITH INFINITE VARIANCE INNOVATIONS

      NARCIS (Netherlands)

      MIKOSCH, T; GADRICH, T; KLUPPELBERG, C; ADLER, RJ

      We consider a standard ARMA process of the form phi(B)X(t) = B(B)Z(t), where the innovations Z(t) belong to the domain of attraction of a stable law, so that neither the Z(t) nor the X(t) have a finite variance. Our aim is to estimate the coefficients of phi and theta. Since maximum likelihood

    16. Relationship between Allan variances and Kalman Filter parameters

      Science.gov (United States)

      Vandierendonck, A. J.; Mcgraw, J. B.; Brown, R. G.

      1984-01-01

      A relationship was constructed between the Allan variance parameters (H sub z, H sub 1, H sub 0, H sub -1 and H sub -2) and a Kalman Filter model that would be used to estimate and predict clock phase, frequency and frequency drift. To start with the meaning of those Allan Variance parameters and how they are arrived at for a given frequency source is reviewed. Although a subset of these parameters is arrived at by measuring phase as a function of time rather than as a spectral density, they all represent phase noise spectral density coefficients, though not necessarily that of a rational spectral density. The phase noise spectral density is then transformed into a time domain covariance model which can then be used to derive the Kalman Filter model parameters. Simulation results of that covariance model are presented and compared to clock uncertainties predicted by Allan variance parameters. A two state Kalman Filter model is then derived and the significance of each state is explained.

    17. Dynamic Programming Using Polar Variance for Image Segmentation.

      Science.gov (United States)

      Rosado-Toro, Jose A; Altbach, Maria I; Rodriguez, Jeffrey J

      2016-10-06

      When using polar dynamic programming (PDP) for image segmentation, the object size is one of the main features used. This is because if size is left unconstrained the final segmentation may include high-gradient regions that are not associated with the object. In this paper, we propose a new feature, polar variance, which allows the algorithm to segment objects of different sizes without the need for training data. The polar variance is the variance in a polar region between a user-selected origin and a pixel we want to analyze. We also incorporate a new technique that allows PDP to segment complex shapes by finding low-gradient regions and growing them. The experimental analysis consisted on comparing our technique with different active contour segmentation techniques on a series of tests. The tests consisted on robustness to additive Gaussian noise, segmentation accuracy with different grayscale images and finally robustness to algorithm-specific parameters. Experimental results show that our technique performs favorably when compared to other segmentation techniques.

    18. Variance Analysis and Adaptive Sampling for Indirect Light Path Reuse

      Institute of Scientific and Technical Information of China (English)

      Hao Qin; Xin Sun; Jun Yan; Qi-Ming Hou; Zhong Ren; Kun Zhou

      2016-01-01

      In this paper, we study the estimation variance of a set of global illumination algorithms based on indirect light path reuse. These algorithms usually contain two passes — in the first pass, a small number of indirect light samples are generated and evaluated, and they are then reused by a large number of reconstruction samples in the second pass. Our analysis shows that the covariance of the reconstruction samples dominates the estimation variance under high reconstruction rates and increasing the reconstruction rate cannot effectively reduce the covariance. We also find that the covariance represents to what degree the indirect light samples are reused during reconstruction. This analysis motivates us to design a heuristic approximating the covariance as well as an adaptive sampling scheme based on this heuristic to reduce the rendering variance. We validate our analysis and adaptive sampling scheme in the indirect light field reconstruction algorithm and the axis-aligned filtering algorithm for indirect lighting. Experiments are in accordance with our analysis and show that rendering artifacts can be greatly reduced at a similar computational cost.

    19. Variance optimal sampling based estimation of subset sums

      CERN Document Server

      Cohen, Edith; Kaplan, Haim; Lund, Carsten; Thorup, Mikkel

      2008-01-01

      From a high volume stream of weighted items, we want to maintain a generic sample of a certain limited size $k$ that we can later use to estimate the total weight of arbitrary subsets. This is the classic context of on-line reservoir sampling, thinking of the generic sample as a reservoir. We present a reservoir sampling scheme providing variance optimal estimation of subset sums. More precisely, if we have seen $n$ items of the stream, then for any subset size $m$, our scheme based on $k$ samples minimizes the average variance over all subsets of size $m$. In fact, the optimality is against any off-line sampling scheme tailored for the concrete set of items seen: no off-line scheme based on $k$ samples can perform better than our on-line scheme when it comes to average variance over any subset size. Our scheme has no positive covariances between any pair of item estimates. Also, our scheme can handle each new item of the stream in $O(\\log k)$ time, which is optimal even on the word RAM.

    20. Estimating Predictive Variance for Statistical Gas Distribution Modelling

      Science.gov (United States)

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

      2009-05-01

      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.

    1. Measuring primordial non-gaussianity without cosmic variance

      CERN Document Server

      Seljak, Uros

      2008-01-01

      Non-gaussianity in the initial conditions of the universe is one of the most powerful mechanisms to discriminate among the competing theories of the early universe. Measurements using bispectrum of cosmic microwave background anisotropies are limited by the cosmic variance, i.e. available number of modes. Recent work has emphasized the possibility to probe non-gaussianity of local type using the scale dependence of large scale bias from highly biased tracers of large scale structure. However, this power spectrum method is also limited by cosmic variance, finite number of structures on the largest scales, and by the partial degeneracy with other cosmological parameters that can mimic the same effect. Here we propose an alternative method that solves both of these problems. It is based on the idea that on large scales halos are biased, but not stochastic, tracers of dark matter: by correlating a highly biased tracer of large scale structure against an unbiased tracer one eliminates the cosmic variance error, wh...

    2. 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.

    3. Genetic Variance for Autism Screening Items in an Unselected Sample of Toddler-Age Twins

      Science.gov (United States)

      Stilp, Rebecca L. H.; Gernsbacher, Morton Ann; Schweigert, Emily K.; Arneson, Carrie L.; Goldsmith, H. Hill

      2010-01-01

      Objective: Twin and family studies of autistic traits and of cases diagnosed with autism suggest high heritability; however, the heritability of autistic traits in toddlers has not been investigated. Therefore, this study's goals were (1) to screen a statewide twin population using items similar to the six critical social and communication items…

    4. Who Is Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety

      Science.gov (United States)

      Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A.; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W.; Lyons, Ian M.; Petrill, Stephen A.

      2014-01-01

      Background: Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving…

    5. Automated Variance Reduction Applied to Nuclear Well-Logging Problems

      Energy Technology Data Exchange (ETDEWEB)

      Wagner, John C [ORNL; Peplow, Douglas E. [ORNL; Evans, Thomas M [ORNL

      2009-01-01

      The Monte Carlo method enables detailed, explicit geometric, energy and angular representations, and hence is considered to be the most accurate method available for solving complex radiation transport problems. Because of its associated accuracy, the Monte Carlo method is widely used in the petroleum exploration industry to design, benchmark, and simulate nuclear well-logging tools. Nuclear well-logging tools, which contain neutron and/or gamma sources and two or more detectors, are placed in boreholes that contain water (and possibly other fluids) and that are typically surrounded by a formation (e.g., limestone, sandstone, calcites, or a combination). The response of the detectors to radiation returning from the surrounding formation is used to infer information about the material porosity, density, composition, and associated characteristics. Accurate computer simulation is a key aspect of this exploratory technique. However, because this technique involves calculating highly precise responses (at two or more detectors) based on radiation that has interacted with the surrounding formation, the transport simulations are computationally intensive, requiring significant use of variance reduction techniques, parallel computing, or both. Because of the challenging nature of these problems, nuclear well-logging problems have frequently been used to evaluate the effectiveness of variance reduction techniques (e.g., Refs. 1-4). The primary focus of these works has been on improving the computational efficiency associated with calculating the response at the most challenging detector location, which is typically the detector furthest from the source. Although the objective of nuclear well-logging simulations is to calculate the response at multiple detector locations, until recently none of the numerous variance reduction methods/techniques has been well-suited to simultaneous optimization of multiple detector (tally) regions. Therefore, a separate calculation is

    6. 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

    7. Estimation of noise-free variance to measure heterogeneity.

      Science.gov (United States)

      Winkler, Tilo; Melo, Marcos F Vidal; Degani-Costa, Luiza H; Harris, R Scott; Correia, John A; Musch, Guido; Venegas, Jose G

      2015-01-01

      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(r)2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13)NN-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.

    8. Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis

      DEFF Research Database (Denmark)

      Loh, Po-Ru; Bhatia, Gaurav; Gusev, Alexander;

      2015-01-01

      Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC...... and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions....... To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale....

    9. Longitudinal analysis of residual feed intake and BW in mink using random regression with heterogeneous residual variance.

      Science.gov (United States)

      Shirali, M; Nielsen, V H; Møller, S H; Jensen, J

      2015-10-01

      The aim of this study was to determine the genetic background of longitudinal residual feed intake (RFI) and BW gain in farmed mink using random regression methods considering heterogeneous residual variances. The individual BW was measured every 3 weeks from 63 to 210 days of age for 2139 male+female pairs of juvenile mink during the growing-furring period. Cumulative feed intake was calculated six times with 3-week intervals based on daily feed consumption between weighing's from 105 to 210 days of age. Genetic parameters for RFI and BW gain in males and females were obtained using univariate random regression with Legendre polynomials containing an animal genetic effect and permanent environmental effect of litter along with heterogeneous residual variances. Heritability estimates for RFI increased with age from 0.18 (0.03, posterior standard deviation (PSD)) at 105 days of age to 0.49 (0.03, PSD) and 0.46 (0.03, PSD) at 210 days of age in male and female mink, respectively. The heritability estimates for BW gain increased with age and had moderate to high range for males (0.33 (0.02, PSD) to 0.84 (0.02, PSD)) and females (0.35 (0.03, PSD) to 0.85 (0.02, PSD)). RFI estimates during the growing period (105 to 126 days of age) showed high positive genetic correlations with the pelting RFI (210 days of age) in male (0.86 to 0.97) and female (0.92 to 0.98). However, phenotypic correlations were lower from 0.47 to 0.76 in males and 0.61 to 0.75 in females. Furthermore, BW records in the growing period (63 to 126 days of age) had moderate (male: 0.39, female: 0.53) to high (male: 0.87, female: 0.94) genetic correlations with pelting BW (210 days of age). The result of current study showed that RFI and BW in mink are highly heritable, especially at the late furring period, suggesting potential for large genetic gains for these traits. The genetic correlations suggested that substantial genetic gain can be obtained by only considering the RFI estimate and BW at pelting

    10. Education modifies genetic and environmental influences on BMI

      DEFF Research Database (Denmark)

      Johnson, Wendy; Kyvik, Kirsten Ohm; Skytthe, Axel

      2011-01-01

      , and education data. Body mass index (BMI = kg weight/ m height(2)) was used to measure degree of obesity. We used quantitative genetic modeling to examine how genetic and shared and nonshared environmental variance in BMI differed by level of education and to estimate how genetic and shared and nonshared...

    11. Extensive pollen flow but few pollen donors and high reproductive variance in an extremely fragmented landscape.

      Directory of Open Access Journals (Sweden)

      Rafael G Albaladejo

      Full Text Available Analysing pollen movement is a key to understanding the reproductive system of plant species and how it is influenced by the spatial distribution of potential mating partners in fragmented populations. Here we infer parameters related to levels of pollen movement and diversity of the effective pollen cloud for the wind-pollinated shrub Pistacia lentiscus across a highly disturbed landscape using microsatellite loci. Paternity analysis and the indirect KinDist and Mixed Effect Mating models were used to assess mating patterns, the pollen dispersal kernel, the effective number of males (N(ep and their relative individual fertility, as well as the existence of fine-scale spatial genetic structure in adult plants. All methods showed extensive pollen movement, with high rates of pollen flow from outside the study site (up to 73-93%, fat-tailed dispersal kernels and large average pollination distances (δ = 229-412 m. However, they also agreed in detecting very few pollen donors (N(ep = 4.3-10.2 and a large variance in their reproductive success: 70% of males did not sire any offspring among the studied female plants and 5.5% of males were responsible for 50% of pollinations. Although we did not find reduced levels of genetic diversity, the adult population showed high levels of biparental inbreeding (14% and strong spatial genetic structure (S(p = 0.012, probably due to restricted seed dispersal and scarce safe sites for recruitment. Overall, limited seed dispersal and the scarcity of successful pollen donors can be contributing to generate local pedigrees and to increase inbreeding, the prelude of genetic impoverishment.

    12. Regression between earthquake magnitudes having errors with known variances

      Science.gov (United States)

      Pujol, Jose

      2016-07-01

      Recent publications on the regression between earthquake magnitudes assume that both magnitudes are affected by error and that only the ratio of error variances is known. If X and Y represent observed magnitudes, and x and y represent the corresponding theoretical values, the problem is to find the a and b of the best-fit line y = a x + b. This problem has a closed solution only for homoscedastic errors (their variances are all equal for each of the two variables). The published solution was derived using a method that cannot provide a sum of squares of residuals. Therefore, it is not possible to compare the goodness of fit for different pairs of magnitudes. Furthermore, the method does not provide expressions for the x and y. The least-squares method introduced here does not have these drawbacks. The two methods of solution result in the same equations for a and b. General properties of a discussed in the literature but not proved, or proved for particular cases, are derived here. A comparison of different expressions for the variances of a and b is provided. The paper also considers the statistical aspects of the ongoing debate regarding the prediction of y given X. Analysis of actual data from the literature shows that a new approach produces an average improvement of less than 0.1 magnitude units over the standard approach when applied to Mw vs. mb and Mw vs. MS regressions. This improvement is minor, within the typical error of Mw. Moreover, a test subset of 100 predicted magnitudes shows that the new approach results in magnitudes closer to the theoretically true magnitudes for only 65 % of them. For the remaining 35 %, the standard approach produces closer values. Therefore, the new approach does not always give the most accurate magnitude estimates.

    13. Critical points of multidimensional random Fourier series: Variance estimates

      Science.gov (United States)

      Nicolaescu, Liviu I.

      2016-08-01

      We investigate the number of critical points of a Gaussian random smooth function uɛ on the m-torus Tm ≔ ℝm/ℤm approximating the Gaussian white noise as ɛ → 0. Let N(uɛ) denote the number of critical points of uɛ. We prove the existence of constants C, C' such that as ɛ goes to zero, the expectation of the random variable ɛmN(uɛ) converges to C, while its variance is extremely small and behaves like C'ɛm.

    14. Generalized Minimum Variance Control for MDOF Structures under Earthquake Excitation

      Directory of Open Access Journals (Sweden)

      Lakhdar Guenfaf

      2016-01-01

      Full Text Available Control of a multi-degree-of-freedom structural system under earthquake excitation is investigated in this paper. The control approach based on the Generalized Minimum Variance (GMV algorithm is developed and presented. Our approach is a generalization to multivariable systems of the GMV strategy designed initially for single-input-single-output (SISO systems. Kanai-Tajimi and Clough-Penzien models are used to generate the seismic excitations. Those models are calculated using the specific soil parameters. Simulation tests using a 3DOF structure are performed and show the effectiveness of the control method.

    15. Stable limits for sums of dependent infinite variance random variables

      DEFF Research Database (Denmark)

      Bartkiewicz, Katarzyna; Jakubowski, Adam; Mikosch, Thomas;

      2011-01-01

      The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to hold are known in the literature. However, most...... of these results are qualitative in the sense that the parameters of the limit distribution are expressed in terms of some limiting point process. In this paper we will be able to determine the parameters of the limiting stable distribution in terms of some tail characteristics of the underlying stationary...

    16. Minimum Variance Beamforming for High Frame-Rate Ultrasound Imaging

      DEFF Research Database (Denmark)

      Holfort, Iben Kraglund; Gran, Fredrik; Jensen, Jørgen Arendt

      2007-01-01

      This paper investigates the application of adaptive beamforming in medical ultrasound imaging. A minimum variance (MV) approach for near-field beamforming of broadband data is proposed. The approach is implemented in the frequency domain, and it provides a set of adapted, complex apodization...... weights for each frequency sub-band. As opposed to the conventional, Delay and Sum (DS) beamformer, this approach is dependent on the specific data. The performance of the proposed MV beamformer is tested on simulated synthetic aperture (SA) ultrasound data, obtained using Field II. For the simulations...

    17. Computing the Expected Value and Variance of Geometric Measures

      DEFF Research Database (Denmark)

      Staals, Frank; Tsirogiannis, Constantinos

      2017-01-01

      points in P. This problem is a crucial part of modern ecological analyses; each point in P represents a species in d-dimensional trait space, and the goal is to compute the statistics of a geometric measure on this trait space, when subsets of species are selected under random processes. We present...... efficient exact algorithms for computing the mean and variance of several geometric measures when point sets are selected under one of the described random distributions. More specifically, we provide algorithms for the following measures: the bounding box volume, the convex hull volume, the mean pairwise...

    18. AVATAR -- Automatic variance reduction in Monte Carlo calculations

      Energy Technology Data Exchange (ETDEWEB)

      Van Riper, K.A.; Urbatsch, T.J.; Soran, P.D. [and others

      1997-05-01

      AVATAR{trademark} (Automatic Variance And Time of Analysis Reduction), accessed through the graphical user interface application, Justine{trademark}, is a superset of MCNP{trademark} that automatically invokes THREEDANT{trademark} for a three-dimensional deterministic adjoint calculation on a mesh independent of the Monte Carlo geometry, calculates weight windows, and runs MCNP. Computational efficiency increases by a factor of 2 to 5 for a three-detector oil well logging tool model. Human efficiency increases dramatically, since AVATAR eliminates the need for deep intuition and hours of tedious handwork.

    19. Multivariate variance targeting in the BEKK-GARCH model

      DEFF Research Database (Denmark)

      Pedersen, Rasmus S.; Rahbæk, 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...... to these two steps. Strong consis-tency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are necessary...

    20. A guide to SPSS for analysis of variance

      CERN Document Server

      Levine, Gustav

      2013-01-01

      This book offers examples of programs designed for analysis of variance and related statistical tests of significance that can be run with SPSS. The reader may copy these programs directly, changing only the names or numbers of levels of factors according to individual needs. Ways of altering command specifications to fit situations with larger numbers of factors are discussed and illustrated, as are ways of combining program statements to request a variety of analyses in the same program. The first two chapters provide an introduction to the use of SPSS, Versions 3 and 4. General rules conce

    1. 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...... show that for this class of processes the optimal endowment and strategy can be expressed more explicitly. The corresponding formulas involve the moment resp. cumulant generating function of the underlying process and a Laplace- or Fourier-type representation of the contingent claim. An example...

    2. Two-dimensional finite-element temperature variance analysis

      Science.gov (United States)

      Heuser, J. S.

      1972-01-01

      The finite element method is extended to thermal analysis by forming a variance analysis of temperature results so that the sensitivity of predicted temperatures to uncertainties in input variables is determined. The temperature fields within a finite number of elements are described in terms of the temperatures of vertices and the variational principle is used to minimize the integral equation describing thermal potential energy. A computer calculation yields the desired solution matrix of predicted temperatures and provides information about initial thermal parameters and their associated errors. Sample calculations show that all predicted temperatures are most effected by temperature values along fixed boundaries; more accurate specifications of these temperatures reduce errors in thermal calculations.

    3. Local orbitals by minimizing powers of the orbital variance

      DEFF Research Database (Denmark)

      Jansik, Branislav; Høst, Stinne; Kristensen, Kasper;

      2011-01-01

      It is demonstrated that a set of local orthonormal Hartree–Fock (HF) molecular orbitals can be obtained for both the occupied and virtual orbital spaces by minimizing powers of the orbital variance using the trust-region algorithm. For a power exponent equal to one, the Boys localization function...... is obtained. For increasing power exponents, the penalty for delocalized orbitals is increased and smaller maximum orbital spreads are encountered. Calculations on superbenzene, C60, and a fragment of the titin protein show that for a power exponent equal to one, delocalized outlier orbitals may...

    4. A Mean-Variance Portfolio Optimal Under Utility Pricing

      Directory of Open Access Journals (Sweden)

      Hürlimann Werner

      2006-01-01

      Full Text Available An expected utility model of asset choice, which takes into account asset pricing, is considered. The obtained portfolio selection problem under utility pricing is solved under several assumptions including quadratic utility, exponential utility and multivariate symmetric elliptical returns. The obtained unique solution, called optimal utility portfolio, is shown mean-variance efficient in the classical sense. Various questions, including conditions for complete diversification and the behavior of the optimal portfolio under univariate and multivariate ordering of risks as well as risk-adjusted performance measurement, are discussed.

    5. Strong genetic overlap between executive functions and intelligence.

      Science.gov (United States)

      Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M

      2016-09-01

      Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record

    6. Genetic and Environmental Bases of Reading and Spelling: A Unified Genetic Dual Route Model

      Science.gov (United States)

      Bates, Timothy C.; Castles, Anne; Luciano, Michelle; Wright, Margaret J.; Coltheart, Max; Martin, Nicholas G.

      2007-01-01

      We develop and test a dual-route model of genetic effects on reading aloud and spelling, based on irregular and non-word reading and spelling performance assessed in 1382 monozygotic and dizygotic twins. As in earlier research, most of the variance in reading was due to genetic effects. However, there were three more specific conclusions: the…

    7. Global genetic variations predict brain response to faces

      DEFF Research Database (Denmark)

      Dickie, Erin W; Tahmasebi, Amir; French, Leon;

      2014-01-01

      Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼ 500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximu...

    8. 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  portfolio and T the length of the time series used to estimate the covariance matrix. At the critical point r  =  1 a phase transition is taking place. The out of sample estimation error blows up at this point as 1/(1  -  r), independently of the covariance matrix or the expected return, displaying the universality not only of the critical exponent, but also the critical point. As a conspicuous illustration of the dangers of in-sample estimates, the optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

    9. 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.

    10. Facial Feature Extraction Method Based on Coefficients of Variances

      Institute of Scientific and Technical Information of China (English)

      Feng-Xi Song; David Zhang; Cai-Kou Chen; Jing-Yu Yang

      2007-01-01

      Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two popular feature ex- traction techniques in statistical pattern recognition field. Due to small sample size problem LDA cannot be directly applied to appearance-based face recognition tasks. As a consequence, a lot of LDA-based facial feature extraction techniques are proposed to deal with the problem one after the other. Nullspace Method is one of the most effective methods among them. The Nullspace Method tries to find a set of discriminant vectors which maximize the between-class scatter in the null space of the within-class scatter matrix. The calculation of its discriminant vectors will involve performing singular value decomposition on a high-dimensional matrix. It is generally memory- and time-consuming. Borrowing the key idea in Nullspace method and the concept of coefficient of variance in statistical analysis we present a novel facial feature extraction method, i.e., Discriminant based on Coefficient of Variance (DCV) in this paper. Experimental results performed on the FERET and AR face image databases demonstrate that DCV is a promising technique in comparison with Eigenfaces, Nullspace Method, and other state-of-the-art facial feature extraction methods.

    11. Cosmic variance of the galaxy cluster weak lensing signal

      CERN Document Server

      Gruen, D; Becker, M R; Friedrich, O; Mana, A

      2015-01-01

      Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M_200m=10^14...10^15 h^-1 M_sol, z=0.25...0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate mass uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ~20 per cent uncertainty from cosmic variance alone at M_200m=10^15 h^-1 M_sol and z=0.25), but significant also...

    12. Mean-Variance-Validation Technique for Sequential Kriging Metamodels

      Energy Technology Data Exchange (ETDEWEB)

      Lee, Tae Hee; Kim, Ho Sung [Hanyang University, Seoul (Korea, Republic of)

      2010-05-15

      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{sub 0} validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean{sub 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.

    13. Infinite Variance in Fermion Quantum Monte Carlo Calculations

      CERN Document Server

      Shi, Hao

      2015-01-01

      For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, lattice QCD calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied upon to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple sub-areas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations turn out to have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calc...

    14. 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...

    15. The Variance of Energy Estimates for the Product Model

      Directory of Open Access Journals (Sweden)

      David Smallwood

      2003-01-01

      , is the product of a slowly varying random window, {w(t}, and a stationary random process, {g(t}, is defined. A single realization of the process will be defined as x(t. This is slightly different from the usual definition of the product model where the window is typically defined as deterministic. An estimate of the energy (the zero order temporal moment, only in special cases is this physical energy of the random process, {x(t}, is defined as m0=∫∞∞|x(t|2dt=∫−∞∞|w(tg(t|2dt Relationships for the mean and variance of the energy estimates, m0, are then developed. It is shown that for many cases the uncertainty (4π times the product of rms duration, Dt, and rms bandwidth, Df is approximately the inverse of the normalized variance of the energy. The uncertainty is a quantitative measure of the expected error in the energy estimate. If a transient has a significant random component, a small uncertainty parameter implies large error in the energy estimate. Attempts to resolve a time/frequency spectrum near the uncertainty limits of a transient with a significant random component will result in large errors in the spectral estimates.

    16. Cosmic variance in the nanohertz gravitational wave background

      CERN Document Server

      Roebber, Elinore; Holz, Daniel; Warren, Michael

      2015-01-01

      We use large N-body simulations and empirical scaling relations between dark matter halos, galaxies, and supermassive black holes to estimate the formation rates of supermassive black hole binaries and the resulting low-frequency stochastic gravitational wave background (GWB). We find this GWB to be relatively insensitive ($\\lesssim10\\%$) to cosmological parameters, with only slight variation between WMAP5 and Planck cosmologies. We find that uncertainty in the astrophysical scaling relations changes the amplitude of the GWB by a factor of $\\sim 2$. Current observational limits are already constraining this predicted range of models. We investigate the Poisson variance in the amplitude of the GWB for randomly-generated populations of supermassive black holes, finding a scatter of order unity per frequency bin below 10 nHz, and increasing to a factor of $\\sim 10$ near 100 nHz. This variance is a result of the rarity of the most massive binaries, which dominate the signal, and acts as a fundamental uncertainty ...

    17. Worldwide variance in the potential utilization of Gamma Knife radiosurgery.

      Science.gov (United States)

      Hamilton, Travis; Dade Lunsford, L

      2016-12-01

      OBJECTIVE The role of Gamma Knife radiosurgery (GKRS) has expanded worldwide during the past 3 decades. The authors sought to evaluate whether experienced users vary in their estimate of its potential use. METHODS Sixty-six current Gamma Knife users from 24 countries responded to an electronic survey. They estimated the potential role of GKRS for benign and malignant tumors, vascular malformations, and functional disorders. These estimates were compared with published disease epidemiological statistics and the 2014 use reports provided by the Leksell Gamma Knife Society (16,750 cases). RESULTS Respondents reported no significant variation in the estimated use in many conditions for which GKRS is performed: meningiomas, vestibular schwannomas, and arteriovenous malformations. Significant variance in the estimated use of GKRS was noted for pituitary tumors, craniopharyngiomas, and cavernous malformations. For many current indications, the authors found significant variance in GKRS users based in the Americas, Europe, and Asia. Experts estimated that GKRS was used in only 8.5% of the 196,000 eligible cases in 2014. CONCLUSIONS Although there was a general worldwide consensus regarding many major indications for GKRS, significant variability was noted for several more controversial roles. This expert opinion survey also suggested that GKRS is significantly underutilized for many current diagnoses, especially in the Americas. Future studies should be conducted to investigate health care barriers to GKRS for many patients.

    18. VARIANCE OF NONLINEAR PHASE NOISE IN FIBER-OPTIC SYSTEM

      Directory of Open Access Journals (Sweden)

      RANJU KANWAR

      2013-04-01

      Full Text Available In communication system, the noise process must be known, in order to compute the system performance. The nonlinear effects act as strong perturbation in long- haul system. This perturbation effects the signal, when interact with amplitude noise, and results in random motion of the phase of the signal. Based on the perturbation theory, the variance of nonlinear phase noise contaminated by both self- and cross-phase modulation, is derived analytically for phase-shift- keying system. Through this work, it is investigated that for longer transmission distance, 40-Gb/s systems are more sensitive to nonlinear phase noise as compared to 50-Gb/s systems. Also, when transmitting the data through the fiber optic link, bit errors are produced due to various effects such as noise from optical amplifiers and nonlinearity occurring in fiber. On the basis of the simulation results , we have compared the bit error rate based on 8-PSK with theoretical results, and result shows that in real time approach, the bit error rate is high for the same signal to noise ratio. MATLAB software is used to validate the analytical expressions for the variance of nonlinear phase noise.

    19. Hidden temporal order unveiled in stock market volatility variance

      Directory of Open Access Journals (Sweden)

      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.

    20. Genetics and implications in perioperative analgesia.

      Science.gov (United States)

      Trescot, Andrea M

      2014-06-01

      The wide range of patient responses to surgical pain, opioids, and anesthetic agents has puzzled anesthesiologists for many years. Much of the variation has been attributed to differences in patient size, technique, or prior drug use. However, recent genetic testing has revealed exciting clues into the basis for these variances, allowing us to start to predict which patients may have difficulties and start to select medications more rationally. In this manuscript, we discuss genetics and pain perception, genetic predisposition to pain, drug metabolism interactions, ethnogenetics, opioid metabolism, opioid receptors, genetic-related peri-anesthetic toxicity, as well as a clinical approach and a discussion regarding the future of genetic testing and anesthesia.

    1. New Genetics

      Science.gov (United States)

      ... Home > Science Education > The New Genetics The New Genetics Living Laboratories Classroom Poster Order a Free Copy ... Piece to a Century-Old Evolutionary Puzzle Computing Genetics Model Organisms RNA Interference The New Genetics is ...

    2. Longitudinal variance-components analysis of the Framingham Heart Study data.

      Science.gov (United States)

      Macgregor, Stuart; Knott, Sara A; White, Ian; Visscher, Peter M

      2003-12-31

      The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.

    3. Quasi equilibrium, variance effective size and fixation index for populations with substructure.

      Science.gov (United States)

      Hössjer, Ola; Ryman, Nils

      2014-11-01

      In this paper, we develop a method for computing the variance effective size N eV, the fixation index F ST and the coefficient of gene differentiation G ST of a structured population under equilibrium conditions. The subpopulation sizes are constant in time, with migration and reproduction schemes that can be chosen with great flexibility. Our quasi equilibrium approach is conditional on non-fixation of alleles. This is of relevance when migration rates are of a larger order of magnitude than the mutation rates, so that new mutations can be ignored before equilibrium balance between genetic drift and migration is obtained. The vector valued time series of subpopulation allele frequencies is divided into two parts; one corresponding to genetic drift of the whole population and one corresponding to differences in allele frequencies among subpopulations. We give conditions under which the first two moments of the latter, after a simple standardization, are well approximated by quantities that can be explicitly calculated. This enables us to compute approximations of the quasi equilibrium values of N eV, F ST and G ST. Our findings are illustrated for several reproduction and migration scenarios, including the island model, stepping stone models and a model where one subpopulation acts as a demographic reservoir. We also make detailed comparisons with a backward approach based on coalescence probabilities.

    4. Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

      DEFF Research Database (Denmark)

      Do, Duy Ngoc; Janss, Luc L G; Strathe, Anders B

      Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition...... genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL had similar accuracy and bias as GBLUP but power parameters had...

    5. Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

      DEFF Research Database (Denmark)

      Do, Duy Ngoc; Janss, L. L. G.; Strathe, Anders Bjerring

      Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition...... genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use...

    6. 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

    7. Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction.

      Science.gov (United States)

      Huang, Ling; Zhang, Hongping; Xu, Peiliang; Geng, Jianghui; Wang, Cheng; Liu, Jingnan

      2017-02-27

      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 × 10(16) 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 new proposed

    8. Interdependence of NAFTA capital markets: A minimum variance portfolio approach

      Directory of Open Access Journals (Sweden)

      López-Herrera Francisco

      2014-01-01

      Full Text Available We estimate the long-run relationships among NAFTA capital market returns and then calculate the weights of a “time-varying minimum variance portfolio” that includes the Canadian, Mexican, and USA capital markets between March 2007 and March 2009, a period of intense turbulence in international markets. Our results suggest that the behavior of NAFTA market investors is not consistent with that of a theoretical “risk-averse” agent during periods of high uncertainty and may be either considered as irrational or attributed to a possible “home country bias”. This finding represents valuable information for portfolio managers and contributes to a better understanding of the nature of the markets in which they invest. It also has practical implications in the design of international portfolio investment policies.

    9. Estimation of measurement variance in the context of environment statistics

      Science.gov (United States)

      Maiti, Pulakesh

      2015-02-01

      The object of environment statistics is for providing information on the environment, on its most important changes over time, across locations and identifying the main factors that influence them. Ultimately environment statistics would be required to produce higher quality statistical information. For this timely, reliable and comparable data are needed. Lack of proper and uniform definitions, unambiguous classifications pose serious problems to procure qualitative data. These cause measurement errors. We consider the problem of estimating measurement variance so that some measures may be adopted to improve upon the quality of data on environmental goods and services and on value statement in economic terms. The measurement technique considered here is that of employing personal interviewers and the sampling considered here is that of two-stage sampling.

    10. Diffusion-Based Trajectory Observers with Variance Constraints

      DEFF Research Database (Denmark)

      Alcocer, Alex; Jouffroy, Jerome; Oliveira, Paulo

      Diffusion-based trajectory observers have been recently proposed as a simple and efficient framework to solve diverse smoothing problems in underwater navigation. For instance, to obtain estimates of the trajectories of an underwater vehicle given position fixes from an acoustic positioning system...... and velocity measurements from a DVL. The observers are conceptually simple and can easily deal with the problems brought about by the occurrence of asynchronous measurements and dropouts. In its original formulation, the trajectory observers depend on a user-defined constant gain that controls the level...... of smoothing and is determined by resorting to trial and error. This paper presents a methodology to choose the observer gain by taking into account a priori information on the variance of the position measurement errors. Experimental results with data from an acoustic positioning system are presented...

    11. Static models, recursive estimators and the zero-variance approach

      KAUST Repository

      Rubino, Gerardo

      2016-01-07

      When evaluating dependability aspects of complex systems, most models belong to the static world, where time is not an explicit variable. These models suffer from the same problems than dynamic ones (stochastic processes), such as the frequent combinatorial explosion of the state spaces. In the Monte Carlo domain, on of the most significant difficulties is the rare event situation. In this talk, we describe this context and a recent technique that appears to be at the top performance level in the area, where we combined ideas that lead to very fast estimation procedures with another approach called zero-variance approximation. Both ideas produced a very efficient method that has the right theoretical property concerning robustness, the Bounded Relative Error one. Some examples illustrate the results.

    12. INTERPRETING MAGNETIC VARIANCE ANISOTROPY MEASUREMENTS IN THE SOLAR WIND

      Energy Technology Data Exchange (ETDEWEB)

      TenBarge, J. M.; Klein, K. G.; Howes, G. G. [Department of Physics and Astronomy, University of Iowa, Iowa City, IA (United States); Podesta, J. J., E-mail: jason-tenbarge@uiowa.edu [Space Science Institute, Boulder, CO (United States)

      2012-07-10

      The magnetic variance anisotropy (A{sub m}) of the solar wind has been used widely as a method to identify the nature of solar wind turbulent fluctuations; however, a thorough discussion of the meaning and interpretation of the A{sub m} has not appeared in the literature. This paper explores the implications and limitations of using the A{sub m} as a method for constraining the solar wind fluctuation mode composition and presents a more informative method for interpreting spacecraft data. The paper also compares predictions of the A{sub m} from linear theory to nonlinear turbulence simulations and solar wind measurements. In both cases, linear theory compares well and suggests that the solar wind for the interval studied is dominantly Alfvenic in the inertial and dissipation ranges to scales of k{rho}{sub i} {approx_equal} 5.

    13. Estimating discharge measurement uncertainty using the interpolated variance estimator

      Science.gov (United States)

      Cohn, T.; Kiang, J.; Mason, R.

      2012-01-01

      Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

    14. MARKOV-MODULATED MEAN-VARIANCE PROBLEM FOR AN INSURER

      Institute of Scientific and Technical Information of China (English)

      Wang Wei; Bi Junna

      2011-01-01

      In this paper, we consider an insurance company which has the option of investing in a risky asset and a risk-free asset, whose price parameters are driven by a finite state Markov chain. The risk process of the insurance company is modeled as a diffusion process whose diffusion and drift parameters switch over time according to the same Markov chain. We study the Markov-modulated mean-variance problem for the insurer and derive explicitly the closed form of the efficient strategy and efficient frontier. In the case of no regime switching, we can see that the efficient frontier in our paper coincides with that of [10] when there is no pure jump.

    15. From Means and Variances to Persons and Patterns

      Directory of Open Access Journals (Sweden)

      James W Grice

      2015-07-01

      Full Text Available A novel approach for conceptualizing and analyzing data from psychological studies is presented and discussed. This approach is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. These models therefore go beyond the variable-based, path models in use today which are limiting with regard to the types of inferences psychologists can draw from their research. In terms of analysis, the newer approach replaces traditional aggregate statistics such as means, variances, and covariances with methods of pattern detection and analysis. While these methods are person-centered and do not require parametric assumptions, they are both demanding and rigorous. They also provide psychologists with the information needed to draw the primary inference they often wish to make from their research; namely, the inference to best explanation.

    16. Mean and variance of coincidence counting with deadtime

      CERN Document Server

      Yu, D F

      2002-01-01

      We analyze the first and second moments of the coincidence-counting process for a system affected by paralyzable (extendable) deadtime with (possibly unequal) deadtimes in each singles channel. We consider both 'accidental' and 'genuine' coincidences, and derive exact analytical expressions for the first and second moments of the number of recorded coincidence events under various scenarios. The results include an exact form for the coincidence rate under the combined effects of decay, background, and deadtime. The analysis confirms that coincidence counts are not exactly Poisson, but suggests that the Poisson statistical model that is used for positron emission tomography image reconstruction is a reasonable approximation since the mean and variance are nearly equal.

    17. Variance of indoor radon concentration: Major influencing factors.

      Science.gov (United States)

      Yarmoshenko, I; Vasilyev, A; Malinovsky, G; Bossew, P; Žunić, Z S; Onischenko, A; Zhukovsky, M

      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.

    18. Risk Management - Variance Minimization or Lower Tail Outcome Elimination

      DEFF Research Database (Denmark)

      Aabo, Tom

      2002-01-01

      This paper illustrates the profound difference between a risk management strategy of variance minimization and a risk management strategy of lower tail outcome elimination. Risk managers concerned about the variability of cash flows will tend to center their hedge decisions on their best guess...... on future cash flows (the budget), while risk managers concerned about costly lower tail outcomes will hedge (considerably) less depending on the level of uncertainty. A risk management strategy of lower tail outcome elimination is in line with theoretical recommendations in a corporate value......-adding perspective. A cross-case study of blue-chip industrial companies partly supports the empirical use of a risk management strategy of lower tail outcome elimination but does not exclude other factors from (co-)driving the observations....

    19. Analysis of variance of an underdetermined geodetic displacement problem

      Energy Technology Data Exchange (ETDEWEB)

      Darby, D.

      1982-06-01

      It has been suggested recently that point displacements in a free geodetic network traversing a strike-slip fault may be estimated from repeated surveys by minimizing only those displacement components normal to the strike. It is desirable to justify this procedure. We construct, from estimable quantities, a deformation parameter which is an F-statistic of the type occurring in the analysis of variance of linear models not of full rank. A test of its significance provides the criterion to justify the displacement solution. It is also interesting to study its behaviour as one varies the supposed strike of the fault. Justification of a displacement solution using data from a strike-slip fault is found, but not for data from a rift valley. The technique can be generalized to more complex patterns of deformation such as those expected near the end-zone of a fault in a dislocation model.

    20. Objective Bayesian Comparison of Constrained Analysis of Variance Models.

      Science.gov (United States)

      Consonni, Guido; Paroli, Roberta

      2016-10-04

      In the social sciences we are often interested in comparing models specified by parametric equality or inequality constraints. For instance, when examining three group means [Formula: see text] through an analysis of variance (ANOVA), a model may specify that [Formula: see text], while another one may state that [Formula: see text], and finally a third model may instead suggest that all means are unrestricted. This is a challenging problem, because it involves a combination of nonnested models, as well as nested models having the same dimension. We adopt an objective Bayesian approach, requiring no prior specification from the user, and derive the posterior probability of each model under consideration. Our method is based on the intrinsic prior methodology, suitably modified to accommodate equality and inequality constraints. Focussing on normal ANOVA models, a comparative assessment is carried out through simulation studies. We also present an application to real data collected in a psychological experiment.

    1. 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...

    2. Correct use of repeated measures analysis of variance.

      Science.gov (United States)

      Park, Eunsik; Cho, Meehye; Ki, Chang-Seok

      2009-02-01

      In biomedical research, researchers frequently use statistical procedures such as the t-test, standard analysis of variance (ANOVA), or the repeated measures ANOVA to compare means between the groups of interest. There are frequently some misuses in applying these procedures since the conditions of the experiments or statistical assumptions necessary to apply these procedures are not fully taken into consideration. In this paper, we demonstrate the correct use of repeated measures ANOVA to prevent or minimize ethical or scientific problems due to its misuse. We also describe the appropriate use of multiple comparison tests for follow-up analysis in repeated measures ANOVA. Finally, we demonstrate the use of repeated measures ANOVA by using real data and the statistical software package SPSS (SPSS Inc., USA).

    3. Hodological resonance, hodological variance, psychosis and schizophrenia: A hypothetical model

      Directory of Open Access Journals (Sweden)

      Paul Brian eLawrie Birkett

      2011-07-01

      Full Text Available Schizophrenia is a disorder with a large number of clinical, neurobiological, and cognitive manifestations, none of which is invariably present. However it appears to be a single nosological entity. This article considers the likely characteristics of a pathology capable of such diverse consequences. It is argued that both deficit and psychotic symptoms can be manifestations of a single pathology. A general model of psychosis is proposed in which the informational sensitivity or responsivity of a network ("hodological resonance" becomes so high that it activates spontaneously, to produce a hallucination, if it is in sensory cortex, or another psychotic symptom if it is elsewhere. It is argued that this can come about because of high levels of modulation such as those assumed present in affective psychosis, or because of high levels of baseline resonance, such as those expected in deafferentation syndromes associated with hallucinations, for example, Charles Bonnet. It is further proposed that schizophrenia results from a process (probably neurodevelopmental causing widespread increases of variance in baseline resonance; consequently some networks possess high baseline resonance and become susceptible to spontaneous activation. Deficit symptoms might result from the presence of networks with increased activation thresholds. This hodological variance model is explored in terms of schizo-affective disorder, transient psychotic symptoms, diathesis-stress models, mechanisms of antipsychotic pharmacotherapy and persistence of genes predisposing to schizophrenia. Predictions and implications of the model are discussed. In particular it suggests a need for more research into psychotic states and for more single case-based studies in schizophrenia.

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

      OpenAIRE

      Hui-qiang Ma

      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...

    5. Understanding the influence of watershed storage caused by human interferences on ET variance

      Science.gov (United States)

      Zeng, R.; Cai, X.

      2014-12-01

      Understanding the temporal variance of evapotranspiration (ET) at the watershed scale remains a challenging task, because it is affected by complex climate conditions, soil properties, vegetation, groundwater and human activities. In a changing environment with extensive and intensive human interferences, understanding ET variance and its factors is important for sustainable water resources management. This study presents an analysis of the effect of storage change caused by human activities on ET variance Irrigation usually filters ET variance through the use of surface and groundwater; however, over-amount irrigation may cause the depletion of watershed storage, which changes the coincidence of water availability and energy supply for ET. This study develops a framework by incorporating the water balance and the Budyko Hypothesis. It decomposes the ET variance to the variances of precipitation, potential ET, catchment storage change, and their covariances. The contributions of ET variance from the various components are scaled by some weighting functions, expressed as long-term climate conditions and catchment properties. ET variance is assessed by records from 32 major river basins across the world. It is found that ET variance is dominated by precipitation variance under hot-dry condition and by evaporative demand variance under cool-wet condition; while the coincidence of water and energy supply controls ET variance under moderate climate condition. Watershed storage change plays an increasing important role in determining ET variance with relatively shorter time scale. By incorporating storage change caused by human interferences, this framework corrects the over-estimation of ET variance in hot-dry climate and under-estimation of ET variance in cool-wet climate. Furthermore, classification of dominant factors on ET variance shows similar patterns as geographic zonation.

    6. Determinants of Neurotransmitters in Cerebrospinal Fluid and Plasma : from Seasonality to Quantitative Genetics

      NARCIS (Netherlands)

      Luykx, J.J.

      2013-01-01

      Most psychiatric conditions are complex genetic as the largest proportion of genetic variance is likely to derive from many genetic variants of small effect. Nonetheless, given the intricacies of the human brain and the heterogeneous nature of psychiatric disease entities, dissecting the genetic mec

    7. Improved variance estimation of maximum likelihood estimators in stable first-order dynamic regression models

      NARCIS (Netherlands)

      Kiviet, J.F.; Phillips, G.D.A.

      2014-01-01

      In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. Using expansion techniques an approximation is obtained to the bias in variance estimation yielding a bias corrected variance estimator. This is achieved for both the standard

    8. A New Approach for Predicting the Variance of Random Decrement Functions

      DEFF Research Database (Denmark)

      Asmussen, J. C.; Brincker, Rune

      1998-01-01

      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...

    9. 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

    10. Modeling Heterogeneous Variance-Covariance Components in Two-Level Models

      Science.gov (United States)

      Leckie, George; French, Robert; Charlton, Chris; Browne, William

      2014-01-01

      Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…

    11. 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

    12. Prediction error variance and expected response to selection, when selection is based on the best predictor - for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

      DEFF Research Database (Denmark)

      Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just

      2002-01-01

      In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...... or random effects). In the different models, expressions are given (when these can be found - otherwise unbiased estimates are given) for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non...... Gaussian traits are generalisations of the well-known formulas for Gaussian traits - and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part...

    13. Genetic algorithms

      Science.gov (United States)

      Wang, Lui; Bayer, Steven E.

      1991-01-01

      Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

    14. Genetic Mapping

      Science.gov (United States)

      ... Fact Sheets Fact Sheets En Español: Mapeo Genético Genetic Mapping What is genetic mapping? How do researchers create ... genetic map? What are genetic markers? What is genetic mapping? Among the main goals of the Human Genome ...

    15. Genetic variation in variability: Phenotypic variability of fledging weight and its evolution in a songbird population.

      Science.gov (United States)

      Mulder, Han A; Gienapp, Philip; Visser, Marcel E

      2016-09-01

      Variation in traits is essential for natural selection to operate and genetic and environmental effects can contribute to this phenotypic variation. From domesticated populations, we know that families can differ in their level of within-family variance, which leads to the intriguing situation that within-family variance can be heritable. For offspring traits, such as birth weight, this implies that within-family variance in traits can vary among families and can thus be shaped by natural selection. Empirical evidence for this in wild populations is however lacking. We investigated whether within-family variance in fledging weight is heritable in a wild great tit (Parus major) population and whether these differences are associated with fitness. We found significant evidence for genetic variance in within-family variance. The genetic coefficient of variation (GCV) was 0.18 and 0.25, when considering fledging weight a parental or offspring trait, respectively. We found a significant quadratic relationship between within-family variance and fitness: families with low or high within-family variance had lower fitness than families with intermediate within-family variance. Our results show that within-family variance can respond to selection and provides evidence for stabilizing selection on within-family variance. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

    16. Genetic evaluation of twenty seed sources of Asparagus racemosus

      Institute of Scientific and Technical Information of China (English)

      Parveen; A Kumar; H.S.Ginwal

      2011-01-01

      A field trial of 20 seed sources of Asparagus racemosus was conducted at the Forest Research Institute, Dehradun, Uttarakhand, India to evaluate their performance of different economic traits. Genotypic variance, phenotypic variance, genotypic coefficient of variance (GCV)and phenotypic coefficient of variance (PCV) for number of shoots,shoot height, shoot weight, number of roots, root length, root diameter and root weight were calculated. Maximum genotypic and phenotypic variance was observed in shoot height among the shoot - related traits and root length among the root - related traits. For the shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance,phenotypic coefficient of variance were 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80,23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among the shoot-related traits and root length among the root-related traits. Index values were developed for all the seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand),Chandigarh (Punjab), Jammu (Jammu and Kashmir) and Solan (Himachal Pradesh), were promising seed sources for root production.

    17. Evidence for genetic control of adult weight plasticity in the snail Helix aspersa

      DEFF Research Database (Denmark)

      Ros, Mathieu; Sorensen, Daniel; Waagepetersen, Rasmus Plenge

      2004-01-01

      Phenotypic plasticity and canalization are important topics in quantitative genetics and evolution. Both concepts are related to environmental sensitivity. The latter can be modeled using a model with genetically structured environmental variance. This work reports the results of a genetic analysis...... of adult weight in the snail Helix aspersa. Several models of heterogeneous variance are fitted using a Bayesin, MCMC approach. Exploratory analyses using posterior predictive model checking and model comparisons based on the deviance information criterion favor a model postulating a genetically structured...... heterogeneous environmental variance. Our analysis provides a strong indication of a positive genetic correlation between additive genetic values affecting the mean and those affecting environmental variation of adult body weight. The possibility of manipulating environmental variance by selection...

    18. A non-zero variance of Tajima's estimator for two sequences even for infinitely many unlinked loci.

      Science.gov (United States)

      King, Léandra; Wakeley, John; Carmi, Shai

      2017-03-21

      The population-scaled mutation rate, θ, is informative on the effective population size and is thus widely used in population genetics. We show that for two sequences and n unlinked loci, the variance of Tajima's estimator (θˆ), which is the average number of pairwise differences, does not vanish even as n→∞. The non-zero variance of θˆ results from a (weak) correlation between coalescence times even at unlinked loci, which, in turn, is due to the underlying fixed pedigree shared by gene genealogies at all loci. We derive the correlation coefficient under a diploid, discrete-time, Wright-Fisher model, and we also derive a simple, closed-form lower bound. We also obtain empirical estimates of the correlation of coalescence times under demographic models inspired by large-scale human genealogies. While the effect we describe is small (Varθˆ∕θ(2)≈ONe(-1)), it is important to recognize this feature of statistical population genetics, which runs counter to commonly held notions about unlinked loci. Copyright © 2017 Elsevier Inc. All rights reserved.

    19. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

      DEFF Research Database (Denmark)

      Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

      2008-01-01

      In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...... in quantitative genetics is to obtain efficient updates of the high-dimensional vectors of genetic random effects and the associated covariance parameters. We discuss various strategies to approach this problem including reparameterization, Langevin-Hastings updates, and updates based on normal approximations....... The methods are compared in applications to Bayesian inference for three data sets using a model with genetically structured variance heterogeneity...

    20. Adenomyosis and Its Variance: Adenomyoma and Female Fertility

      Directory of Open Access Journals (Sweden)

      Peng-Hui Wang

      2009-09-01

      Full Text Available Extensive adenomyosis (adenomyosis or its variance, localized adenomyosis (adenomyoma of the uterus, is often described as scattered, widely-distributed endometrial glands or stromal tissue found throughout the myometrium layer of the uterus. By definition, adenomyosis consists of epithelial as well as stromal elements, and is situated at least 2.5 mm below the endometrial–myometrial junction. However, the diagnosis and clinical significance of uterine adenomyosis and/or adenomyoma remain somewhat enigmatic. The relationship between infertility and uterine adenomyosis and/or adenomyoma is still uncertain, but severe endometriosis impairs the chances of successful pregnancy when using artificial reproductive techniques. To date, there is no uniform agreement on the most appropriate therapeutic methods for managing women with uterine adenomyosis and/or adenomyoma who want to preserve their fertility. Fertility has been restored after successful treatment of adenomyosis using multiple modalities, including hormonal therapy and conservative surgical therapy via laparoscopy or exploratory laparotomy, uterine artery embolization, and other methods, including a potential but under- investigated procedure, magnetic resonance-guided focused ultrasound. This review will explore recent publications that have addressed the use of different approaches in the management of subfertile women with uterine adenomyosis and adenomyoma.

    1. Cosmic variance and the measurement of the local Hubble parameter.

      Science.gov (United States)

      Marra, Valerio; Amendola, Luca; Sawicki, Ignacy; Valkenburg, Wessel

      2013-06-14

      There is an approximately 9% discrepancy, corresponding to 2.4 σ, between two independent constraints on the expansion rate of the Universe: one indirectly arising from the cosmic microwave background and baryon acoustic oscillations and one more directly obtained from local measurements of the relation between redshifts and distances to sources. We argue that by taking into account the local gravitational potential at the position of the observer this tension--strengthened by the recent Planck results--is partially relieved and the concordance of the Standard Model of cosmology increased. We estimate that measurements of the local Hubble constant are subject to a cosmic variance of about 2.4% (limiting the local sample to redshifts z > 0.010) or 1.3% (limiting it to z > 0.023), a more significant correction than that taken into account already. Nonetheless, we show that one would need a very rare fluctuation to fully explain the offset in the Hubble rates. If this tension is further strengthened, a cosmology beyond the Standard Model may prove necessary.

    2. Sparse recovery with unknown variance: a LASSO-type approach

      CERN Document Server

      Chretien, Stephane

      2011-01-01

      We address the issue of estimating the regression vector $\\beta$ and the variance $\\sg^{2}$ in the generic s-sparse linear model $y = X\\beta+z$, with $\\beta\\in\\R^{p}$, $y\\in\\R^{n}$, $z\\sim\\mathcal N(0,\\sg^2 I)$ and $p> n$. We propose a new LASSO-type method that jointly estimates $\\beta$, $\\sg^{2}$ and the relaxation parameter $\\lb$ by imposing an explicit trade-off constraint between the $\\log$-likelihood and $\\ell_1$-penalization terms. We prove that exact recovery of the support and sign pattern of $\\beta$ holds with probability at least $1-O(p^{-\\alpha})$. Our assumptions, parametrized by $\\alpha$, are similar to the ones proposed in \\cite{CandesPlan:AnnStat09} for $\\sg^{2}$ known. The proof relies on a tail decoupling argument with explicit constants and a recent version of the Non-Commutative Bernstein inequality \\cite{Tropp:ArXiv10}. Our result is then derived from the optimality conditions for the estimators of $\\beta$ and $\\lb$. Finally, a thorough analysis of the standard LASSO estimator as a functi...

    3. Analysis of variance in neuroreceptor ligand imaging studies.

      Directory of Open Access Journals (Sweden)

      Ji Hyun Ko

      Full Text Available Radioligand positron emission tomography (PET with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA, and examine its feasibility using simulated [(11C]raclopride PET data. We also re-visit data from our previously published [(11C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies.

    4. Chromatic visualization of reflectivity variance within hybridized directional OCT images

      Science.gov (United States)

      Makhijani, Vikram S.; Roorda, Austin; Bayabo, Jan Kristine; Tong, Kevin K.; Rivera-Carpio, Carlos A.; Lujan, Brandon J.

      2013-03-01

      This study presents a new method of visualizing hybridized images of retinal spectral domain optical coherence tomography (SDOCT) data comprised of varied directional reflectivity. Due to the varying reflectivity of certain retinal structures relative to angle of incident light, SDOCT images obtained with differing entry positions result in nonequivalent images of corresponding cellular and extracellular structures, especially within layers containing photoreceptor components. Harnessing this property, cross-sectional pathologic and non-pathologic macular images were obtained from multiple pupil entry positions using commercially-available OCT systems, and custom segmentation, alignment, and hybridization algorithms were developed to chromatically visualize the composite variance of reflectivity effects. In these images, strong relative reflectivity from any given direction visualizes as relative intensity of its corresponding color channel. Evident in non-pathologic images was marked enhancement of Henle's fiber layer (HFL) visualization and varying reflectivity patterns of the inner limiting membrane (ILM) and photoreceptor inner/outer segment junctions (IS/OS). Pathologic images displayed similar and additional patterns. Such visualization may allow a more intuitive understanding of structural and physiologic processes in retinal pathologies.

    5. Analysis of variance (ANOVA) models in lower extremity wounds.

      Science.gov (United States)

      Reed, James F

      2003-06-01

      Consider a study in which 2 new treatments are being compared with a control group. One way to compare outcomes would simply be to compare the 2 treatments with the control and the 2 treatments against each using 3 Student t tests (t test). If we were to compare 4 treatment groups, then we would need to use 6 t tests. The difficulty with using multiple t tests is that as the number of groups increases, so will the likelihood of finding a difference between any pair of groups simply by change when no real difference exists by definition a Type I error. If we were to perform 3 separate t tests each at alpha = .05, the experimental error rate increases to .14. As the number of multiple t tests increases, the experiment-wise error rate increases rather rapidly. The solution to the experimental error rate problem is to use analysis of variance (ANOVA) methods. Three basic ANOVA designs are reviewed that give hypothetical examples drawn from the literature to illustrate single-factor ANOVA, repeated measures ANOVA, and randomized block ANOVA. "No frills" SPSS or SAS code for each of these designs and examples used are available from the author on request.

    6. Variance in Dominant Grain Size Across the Mississippi River Delta

      Science.gov (United States)

      Miller, K. L.; Chamberlain, E. L.; Esposito, C. R.; Wagner, R. W.; Mohrig, D. C.

      2016-02-01

      Proposals to restore coastal Louisiana often center on Mississippi River diversion projects wherein water and sediment are routed into wetlands and shallow waters in an effort to build land. Successful design and implementation of diversions will include consideration of behavior and characteristics of sediment, both in the river and in the receiving basin. The Mississippi River sediment load is primarily mud (roughly 75%), with the remainder being very-fine to medium sand or organic detritus. The dominance of muds leads many to suggest that diversions should focus on capturing the mud fraction despite the smaller size and longer settling times required for these particles compared to sand; others believe that sand should be the focus. We present a systemic analysis of the texture of land-building sediment in the Mississippi Delta using borehole data from various depositional environments representing a range of spatial scales, system ages, and fluvial and basin characteristics. We include subdelta-scale data from the incipient Wax Lake Delta and from the distal plain of the abandoned Lafourche subdelta, as well as crevasse-scale data from modern Cubit's Gap and the Attakapas splay, an inland Lafourche crevasse. Comparison of these sites demonstrates a large variance in the volumetric mud to sand ratios across the system. We consider the differences to be emblematic of the various forcings on each lobe as it formed and suggest that the most efficient building block for a diversion is a function of the receiving basin and is not uniform across the entire delta.

    7. On Eliminating The Scrambling Variance In Scrambled Response Models

      Directory of Open Access Journals (Sweden)

      Zawar Hussain

      2012-06-01

      Full Text Available To circumvent the response bias in sensitive surveys randomized response models are being used. To add into it we propose an improved response model utilizing both the additive and multiplicative scrambling method. The proposed model provides greater flexibility in terms of fixing the constantKdepending upon the guessed distribution of sensitive variable and nature of the population. The proposed model yields an unbiased estimator and is anticipated as more protective against the privacy of the respondents. The relative efficiency comparison of the proposed estimator is made relative to Hussain and Shabbir (2007 RRM. Furthermore, the proposed model itself is improved by taking the two responses from each respondent and suggesting a weighted estimator yielding an unbiased estimator having the minimum possible sampling variance. The suggested weighted estimator is unconditionally more efficient than all of the suggested estimators until now. Future research may be focused on privacy protection provided by the scrambling models. More scrambling models may be identified and improved by taking the two responses from each respondent in such a way that the scrambling effect is balanced out.

    8. 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.

    9. Identifiability of Gaussian Structural Equation Models with Same Error Variances

      CERN Document Server

      Peters, Jonas

      2012-01-01

      We consider structural equation models (SEMs) in which variables can be written as a function of their parents and noise terms (the latter are assumed to be jointly independent). Corresponding to each SEM, there is a directed acyclic graph (DAG) G_0 describing the relationships between the variables. In Gaussian SEMs with linear functions, the graph can be identified from the joint distribution only up to Markov equivalence classes (assuming faithfulness). It has been shown, however, that this constitutes an exceptional case. In the case of linear functions and non-Gaussian noise, the DAG becomes identifiable. Apart from few exceptions the same is true for non-linear functions and arbitrarily distributed additive noise. In this work, we prove identifiability for a third modification: if we require all noise variables to have the same variances, again, the DAG can be recovered from the joint Gaussian distribution. Our result can be applied to the problem of causal inference. If the data follow a Gaussian SEM w...

    10. Cosmic variance in [O/Fe] in the Galactic disk

      CERN Document Server

      de Lis, S Bertran; Majewski, S R; Schiavon, R P; Holtzman, J A; Shetrone, M; Carrera, R; Pérez, A E García; Mészáros, Sz; Frinchaboy, P M; Hearty, F R; Nidever, D L; Zasowski, G; Ge, J

      2016-01-01

      We examine the distribution of the [O/Fe] abundance ratio in stars across the Galactic disk using H-band spectra from the Apache Point Galactic Evolution Experiment (APOGEE). We minimized systematic errors by considering groups of stars with similar atmospheric parameters. The APOGEE measurements in the Sloan Digital Sky Survey Data Release 12 reveal that the square root of the star-to-star cosmic variance in oxygen at a given metallicity is about 0.03-0.04 dex in both the thin and thick disk. This is about twice as high as the spread found for solar twins in the immediate solar neighborhood and is probably caused by the wider range of galactocentric distances spanned by APOGEE stars. We quantified measurement uncertainties by examining the spread among stars with the same parameters in clusters; these errors are a function of effective temperature and metallicity, ranging between 0.005 dex at 4000 K and solar metallicity, to about 0.03 dex at 4500 K and [Fe/H]= -0.6. We argue that measuring the spread in [O/...

    11. Cosmic variance in [O/Fe] in the Galactic disk

      Science.gov (United States)

      Bertran de Lis, S.; Allende Prieto, C.; Majewski, S. R.; Schiavon, R. P.; Holtzman, J. A.; Shetrone, M.; Carrera, R.; García Pérez, A. E.; Mészáros, Sz.; Frinchaboy, P. M.; Hearty, F. R.; Nidever, D. L.; Zasowski, G.; Ge, J.

      2016-05-01

      We examine the distribution of the [O/Fe] abundance ratio in stars across the Galactic disk using H-band spectra from the Apache Point Galactic Evolution Experiment (APOGEE). We minimize systematic errors by considering groups of stars with similar atmospheric parameters. The APOGEE measurements in the Sloan Digital Sky Survey data release 12 reveal that the square root of the star-to-star cosmic variance in the oxygen-to-iron ratio at a given metallicity is about 0.03-0.04 dex in both the thin and thick disk. This is about twice as high as the spread found for solar twins in the immediate solar neighborhood and the difference is probably associated to the wider range of galactocentric distances spanned by APOGEE stars. We quantify the uncertainties by examining the spread among stars with the same parameters in clusters; these errors are a function of effective temperature and metallicity, ranging between 0.005 dex at 4000 K and solar metallicity, to about 0.03 dex at 4500 K and [Fe/H] ≃ -0.6. We argue that measuring the spread in [O/Fe] and other abundance ratios provides strong constraints for models of Galactic chemical evolution.

    12. Designing electricity generation portfolios using the mean-variance approach

      Directory of Open Access Journals (Sweden)

      Jorge Cunha

      2014-06-01

      Full Text Available The use of the mean-variance approach (MVA is well demonstrated in the financial literature for the optimal design of financial assets portfolios. The electricity sector portfolios are also guided by similar objectives, namely maximizing return and minimizing risk. As such, this paper proposes two possible MVA for the design of optimal renewable electricity production portfolios. The first approach is directed to portfolio output maximization and the second one is directed to portfolio cost optimization. The models implementation was achieved from data obtained for each quarter of an hour for a time period close to four years for the Portuguese electricity system. A set of renewable energy sources (RES portfolios was obtained, mixing three RES technologies, namely hydro power, wind power and photovoltaic. This allowed to recognize the seasonality of the resources demonstrating that hydro power output is positively correlated with wind and that photovoltaic is negatively correlated with both hydro and wind. The results showed that for both models the less risky solutions are characterised by a mix of RES technologies, taking advantage of the diversification benefits. As for the highest return solutions, as expected those were the ones with higher risk but the portfolio composition largely depends on the assumed costs of each technology.

    13. A model selection approach to analysis of variance and covariance.

      Science.gov (United States)

      Alber, Susan A; Weiss, Robert E

      2009-06-15

      An alternative to analysis of variance is a model selection approach where every partition of the treatment means into clusters with equal value is treated as a separate model. The null hypothesis that all treatments are equal corresponds to the partition with all means in a single cluster. The alternative hypothesis correspond to the set of all other partitions of treatment means. A model selection approach can also be used for a treatment by covariate interaction, where the null hypothesis and each alternative correspond to a partition of treatments into clusters with equal covariate effects. We extend the partition-as-model approach to simultaneous inference for both treatment main effect and treatment interaction with a continuous covariate with separate partitions for the intercepts and treatment-specific slopes. The model space is the Cartesian product of the intercept partition and the slope partition, and we develop five joint priors for this model space. In four of these priors the intercept and slope partition are dependent. We advise on setting priors over models, and we use the model to analyze an orthodontic data set that compares the frictional resistance created by orthodontic fixtures. Copyright (c) 2009 John Wiley & Sons, Ltd.

    14. Analysis of variance in neuroreceptor ligand imaging studies.

      Science.gov (United States)

      Ko, Ji Hyun; Reilhac, Anthonin; Ray, Nicola; Rusjan, Pablo; Bloomfield, Peter; Pellecchia, Giovanna; Houle, Sylvain; Strafella, Antonio P

      2011-01-01

      Radioligand positron emission tomography (PET) with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA), and examine its feasibility using simulated [(11)C]raclopride PET data. We also re-visit data from our previously published [(11)C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies.

    15. Cosmological N-body simulations with suppressed variance

      Science.gov (United States)

      Angulo, Raul E.; Pontzen, Andrew

      2016-10-01

      We present and test a method that dramatically reduces variance arising from the sparse sampling of wavemodes in cosmological simulations. The method uses two simulations which are fixed (the initial Fourier mode amplitudes are fixed to the ensemble average power spectrum) and paired (with initial modes exactly out of phase). We measure the power spectrum, monopole and quadrupole redshift-space correlation functions, halo mass function and reduced bispectrum at z = 1. By these measures, predictions from a fixed pair can be as precise on non-linear scales as an average over 50 traditional simulations. The fixing procedure introduces a non-Gaussian correction to the initial conditions; we give an analytic argument showing why the simulations are still able to predict the mean properties of the Gaussian ensemble. We anticipate that the method will drive down the computational time requirements for accurate large-scale explorations of galaxy bias and clustering statistics, and facilitating the use of numerical simulations in cosmological data interpretation.

    16. Random and fixed effects in plant genetics.

      Science.gov (United States)

      Cockerham, C C

      1980-05-01

      A general model for any type of genetic entry is developed which takes into account both the factorial model of gene effects and the ancestral sources, whether inbred lines or outbred varieties, of the genes.Utilizing the model, various genetic designs of fixed entries are explored for the estimation of genetic effects and the testing of genetic hypotheses. These designs consisted of generation means - parents, crosses, various types of backcrosses, and so on - stemming from one or more pairs of parents, and of hybrid combinations from factorial mating designs. Limitations, from the standpoint of genetic effects that can be estimated and genetic hypotheses that can be tested, are developed in considerable detail.When entries from the factorial mating designs are considered to be random, attention is focused on the estimation of genetic variances, rather than effects, and on the concomitant changes in the tests of genetic hypotheses. While there is considerable improvement over fixed entries in the number of types of genetic variances that can be estimated, and of genetic hypotheses that can be tested, they are still very limited in contrast to what would be most desirable.

    17. Genetic Counseling

      Science.gov (United States)

      Genetic counseling provides information and support to people who have, or may be at risk for, genetic disorders. A ... meets with you to discuss genetic risks. The counseling may be for yourself or a family member. ...

    18. Predicting genetics achievement in nonmajors college biology

      Science.gov (United States)

      Mitchell, Angela; Lawson, Anton E.

      Students enrolled in a non-majors college biology course were pretested to determine their level of intellectual development, degree of field independence, mental capacity, amount of prior genetics knowledge, and amount of fluid intelligence. They were then taught a unit on Mendelian genetics. The only student variables found to not account for a significant amount of variance on a test of reading comprehension and/or a test of genetics achievement was amount of prior genetics knowledge. Developmental level was found to be the most consistent predictor of performance, suggesting that a lack of general hypothetico-deductive reasoning ability is a major factor limiting achievement among these students.

    19. 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.

    20. Principal component approach in variance component estimation for international sire evaluation

      Directory of Open Access Journals (Sweden)

      Jakobsen Jette

      2011-05-01

      Full Text Available Abstract Background The dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model. Methods This article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC and the so-called bottom-up REML approach (bottom-up PC, in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (covariance matrix. Results Our study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (covariance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in