Evolution of Genetic Variance during Adaptive Radiation.
Walter, Greg M; Aguirre, J David; Blows, Mark W; Ortiz-Barrientos, Daniel
2018-04-01
Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.
Genetic variants influencing phenotypic variance heterogeneity.
Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa
2018-03-01
Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.
variance components and genetic parameters for live weight
African Journals Online (AJOL)
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Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.
Comparing estimates of genetic variance across different relationship models.
Legarra, Andres
2016-02-01
Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.
Heritability, variance components and genetic advance of some ...
African Journals Online (AJOL)
Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.
Genetic variance components for residual feed intake and feed ...
African Journals Online (AJOL)
Feeding costs of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce feeding cost in beef cattle and thereby improve profitability. This study estimated genetic (co)variances between weaning weight and other production, reproduction ...
Genetic and environmental variance in content dimensions of the MMPI.
Rose, R J
1988-08-01
To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.
Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.
Zapko-Willmes, Alexandra; Kandler, Christian
2018-01-01
The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.
Analysis of conditional genetic effects and variance components in developmental genetics.
Zhu, J
1995-12-01
A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.
Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L
2017-10-01
Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.
Argentine Population Genetic Structure: Large Variance in Amerindian Contribution
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
Dominance genetic variance for traits under directional selection in Drosophila serrata.
Sztepanacz, Jacqueline L; Blows, Mark W
2015-05-01
In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.
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
Variance components and genetic parameters for body weight and ...
African Journals Online (AJOL)
model included a direct as well as a maternal additive genetic effect, while only the direct additive genetic eff'ect had a sig- .... deviations from the log likelihood value obtained under the ... (1995).lt would therefore be fair to assume that a.
Genetic control of residual variance of yearling weight in Nellore beef cattle.
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 (Box-Cox transformation was able to decrease the dependence of the 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
Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.
Yang, Ye; Christensen, Ole F; Sorensen, Daniel
2011-02-01
Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.
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
Genetic factors explain half of all variance in serum eosinophil cationic protein
DEFF Research Database (Denmark)
Elmose, Camilla; Sverrild, Asger; van der Sluis, Sophie
2014-01-01
with variation in serum ECP and to determine the relative proportion of the variation in ECP due to genetic and non-genetic factors, in an adult twin sample. METHODS: A sample of 575 twins, selected through a proband with self-reported asthma, had serum ECP, lung function, airway responsiveness to methacholine......, exhaled nitric oxide, and skin test reactivity, measured. Linear regression analysis and variance component models were used to study factors associated with variation in ECP and the relative genetic influence on ECP levels. RESULTS: Sex (regression coefficient = -0.107, P ... was statistically non-significant (r = -0.11, P = 0.50). CONCLUSION: Around half of all variance in serum ECP is explained by genetic factors. Serum ECP is influenced by sex, BMI, and airway responsiveness. Serum ECP and airway responsiveness seem not to share genetic variance....
Genetic variance of Trichomonas vaginalis isolates by Southern hybridization
Ryu, Jae-Sook; Min, Duk-Young; Shin, Myeong-Heon; Cho, Youl-Hee
1998-01-01
In the present study, genomic DNAs were purified from Korean isolates (KT8, KT6, KT-Kim and KT-Lee) and foreign strains (CDC85, IR78 and NYH 286) of Trichomonas vaginalis, and hybridized with a probe based on the repetitive sequence cloned from T. vaginalis to observe the genetic differences. By Southern hybridization, all isolates of T. vaginalis except the NYH286 strain had 11 bands. Therefore all isolates examined were distinguishable into 3 groups according to their banding patterns; i) K...
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...
Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).
Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars
2013-10-17
Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro
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
Genetic variance for uniformity of harvest weight in Nile tilapia (Oreochromis niloticus)
Khaw, H.L.; Ponzoni, R.W.; Yee, H.Y.; Aziz, M.A.; Mulder, H.A.; Marjanovic, J.; Bijma, P.
2016-01-01
Competition for resources is common in aquaculture, which inflates the variability of fish body weight. Selective breeding is one of the effective approaches that may enable a reduction of size variability (or increase in uniformity) for body weight by genetic means. The genetic variance of
Selection for uniformity in livestock by exploiting genetic heterogeneity of environmental variance
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,
Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance
Mulder, H.A.; Veerkamp, R.F.; Vereijken, A.; Bijma, P.; Hill, W.G.
2008-01-01
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,
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.
Stock, Amanda J; Campitelli, Brandon E; Stinchcombe, John R
2014-08-19
Clinal variation is commonly interpreted as evidence of adaptive differentiation, although clines can also be produced by stochastic forces. Understanding whether clines are adaptive therefore requires comparing clinal variation to background patterns of genetic differentiation at presumably neutral markers. Although this approach has frequently been applied to single traits at a time, we have comparatively fewer examples of how multiple correlated traits vary clinally. Here, we characterize multivariate clines in the Ivyleaf morning glory, examining how suites of traits vary with latitude, with the goal of testing for divergence in trait means that would indicate past evolutionary responses. We couple this with analysis of genetic variance in clinally varying traits in 20 populations to test whether past evolutionary responses have depleted genetic variance, or whether genetic variance declines approaching the range margin. We find evidence of clinal differentiation in five quantitative traits, with little evidence of isolation by distance at neutral loci that would suggest non-adaptive or stochastic mechanisms. Within and across populations, the traits that contribute most to population differentiation and clinal trends in the multivariate phenotype are genetically variable as well, suggesting that a lack of genetic variance will not cause absolute evolutionary constraints. Our data are broadly consistent theoretical predictions of polygenic clines in response to shallow environmental gradients. Ecologically, our results are consistent with past findings of natural selection on flowering phenology, presumably due to season-length variation across the range. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Use of genomic models to study genetic control of environmental variance
DEFF Research Database (Denmark)
Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel
2011-01-01
. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...
DEFF Research Database (Denmark)
van Heerwaarden, Belinda; Willi, Yvonne; Kristensen, Torsten N
2008-01-01
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...
Genetic control of residual variance of yearling weight in nellore beef cattle
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
Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin
2017-12-01
A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.
Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig
2018-05-01
As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.
Ramakers, J.J.C.; Culina, A.; Visser, M.E.; Gienapp, P.
2017-01-01
Additive genetic variance and selection are the key ingredients for evolution. In wild populations, however, predicting evolutionary trajectories is difficult, potentially by an unrecognised underlying environment dependency of both (additive) genetic variance and selection (i.e. G×E and S×E).
Increasing the genetic variance of rice protein through mutation breeding techniques
International Nuclear Information System (INIS)
Ismachin, M.
1975-01-01
Recommended rice variety in Indonesia, Pelita I/1 was treated with gamma rays at the doses of 20 krad, 30 krad, and 40 krad. The seeds were also treated with EMS 1%. In M 2 generation, the protein content of seeds from the visible mutants and from the normal looking plants were analyzed by DBC method. No significant increase in the genetic variance was found on the samples treated with 20 krad gamma, and on the normal looking plants treated by EMS 1%. The mean value of the treated samples were mostly significant decrease compared with the mean value of the protein distribution in untreated samples (control). Since significant increase in genetic variance was also found in M 2 normal looking plants - treated with gamma at the doses of 30 krad and 40 krad -selection of protein among these materials could be more valuable. (author)
The genetic variance of resistance in M3 lines of rice against leaf blight disease
International Nuclear Information System (INIS)
Mugiono
1979-01-01
Seeds of Pelita I/1 rice variety were irradiated with 20, 30, 40 and 50 krad of gamma rays from a 60 Co source. Plants of M 3 lines were inoculated with bacterial leaf blight, Xanthomonas oryzae (Uzeda and Ishiyama) Downson, using clipping method. The coefficient of genetic variability of resistance against leaf blight disease increased with increasing dose. Highly significant difference in the genetic variance of resistance were found between the treated samples and the control. Dose of 20 krad gave good probability for selection of plants resistant against leaf blight disease. (author)
Bjørnerem, Åshild; Bui, Minh; Wang, Xiaofang; Ghasem-Zadeh, Ali; Hopper, John L; Zebaze, Roger; Seeman, Ego
2015-03-01
All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ = 0.49) than DZ (rDZ = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling markers more because of differences in their genetic factors than
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.
Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes.
Cottle, D J; Gilmour, A R; Pabiou, T; Amer, P R; Fahey, A G
2016-04-01
It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (VE ) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep. © 2015 Blackwell Verlag GmbH.
Directory of Open Access Journals (Sweden)
Abdulqader Jighly
2018-02-01
Full Text Available Whole genome duplication (WGD is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome. The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy
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.
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 available...... for research purposes at http://www.bdporc.irta.es/estudis.jsp. The main feature of the program is to compute Monte Carlo estimates of marginal posterior distributions of parameters of interest. The program is quite flexible, allowing the user to fit a variety of linear models at the level of the mean...
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.
Sztepanacz, Jacqueline L; Rundle, Howard D
2012-10-01
Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank
2018-03-22
Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.
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...
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 ...
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
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...
Mulder, H.A.; Crump, R.E.; Calus, M.P.L.; Veerkamp, R.F.
2013-01-01
In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean
Husby, A.; Visser, M.E.; Kruuk, L.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
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.
Directory of Open Access Journals (Sweden)
Guosheng Su
Full Text Available 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, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness 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 (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.
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Francisco Garcia-Gonzalez
2011-01-01
Full Text Available Whether species exhibit significant heritable variation in fitness is central for sexual selection. According to good genes models there must be genetic variation in males leading to variation in offspring fitness if females are to obtain genetic benefits from exercising mate preferences, or by mating multiply. However, sexual selection based on genetic benefits is controversial, and there is limited unambiguous support for the notion that choosy or polyandrous females can increase the chances of producing offspring with high viability. Here we examine the levels of additive genetic variance in two fitness components in the dung beetle Onthophagus taurus. We found significant sire effects on egg-to-adult viability and on son, but not daughter, survival to sexual maturity, as well as moderate coefficients of additive variance in these traits. Moreover, we do not find evidence for sexual antagonism influencing genetic variation for fitness. Our results are consistent with good genes sexual selection, and suggest that both pre- and postcopulatory mate choice, and male competition could provide indirect benefits to females.
Shared genetic variance between the features of the metabolic syndrome: Heritability studies
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
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities
Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.
2009-01-01
Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…
Who is afraid of math? Two sources of genetic variance for mathematical anxiety.
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.
Increased genetic variance of BMI with a higher prevalence of obesity
DEFF Research Database (Denmark)
Rokholm, Benjamin; Silventoinen, Karri; Ängquist, Lars
2011-01-01
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....
Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety
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
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...... records exist for the parents). Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to the sire-dam model). Conclusions The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal...... 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...
Smit, D.J.A.; Boomsma, D.I.; Schnack, H.G.; Hulshoff Pol, H.E.; de Geus, E.J.C.
2012-01-01
The human electroencephalogram (EEG) consists of oscillations that reflect the summation of postsynaptic potentials at the dendritic tree of cortical neurons. The strength of the oscillations (EEG power) is a highly genetic trait that has been related to individual differences in many phenotypes,
Potato breeding cycles typically last 6-7 years because of the modest seed multiplication rate and large number of traits required of new varieties. Genomic selection has the potential to increase genetic gain per unit of time, through higher accuracy and/or a shorter cycle. Both possibilities were ...
Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F
2013-01-01
In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the
Directory of Open Access Journals (Sweden)
Lejla Lasić
2013-02-01
Full Text Available There are two major theories for inheritance of Rh blood group system: Fisher - Race theory and Wiener theory. Aim of this study was identifying frequency of RHDCE alleles in Bosnian - Herzegovinian population and introduction of this method in screening for Rh phenotype in B&H since this type of analysis was not used for blood typing in B&H before. Rh blood group was typed by Polymerase Chain Reaction, using the protocols and primers previously established by other authors, then carrying out electrophoresis in 2-3% agarose gel. Percentage of Rh positive individuals in our sample is 84.48%, while the percentage of Rh negative individuals is 15.52%. Inter-rater agreement statistic showed perfect agreement (K=1 between the results of Rh blood system detection based on serological and molecular-genetics methods. In conclusion, molecular - genetic methods are suitable for prenatal genotyping and specific cases while standard serological method is suitable for high-throughput of samples.
Benavente, Javiera N; Seeb, Lisa W; Seeb, James E; Arismendi, Ivan; Hernández, Cristián E; Gajardo, Gonzalo; Galleguillos, Ricardo; Cádiz, Maria I; Musleh, Selim S; Gomez-Uchida, Daniel
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 substantial
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
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).
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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.
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Gebregziabher Gebreyohannes
2013-09-01
Full Text Available The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY, lactation length (LL, average milk yield per day (YD, initial milk yield (IY, peak milk yield (PY, days to peak (DP and parameters (ln(a and c of the modified incomplete gamma function (MIG in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus Boran (B and Horro (H and their crosses with different fractions of Friesian (F, Jersey (J and Simmental (S. There were 23 breed groups (B, H, and their crossbreds with F, J, and S in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001 by the considered fixed effects. High grade B×F cows (3/16B 13/16F had the highest least squares means (LSM for LY (2,490±178.9 kg, IY (10.5±0.8 kg, PY (12.7±0.9 kg, YD (7.6±0.55 kg and LL (361.4±31.2 d, while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses
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Kaifeng Ma
2018-01-01
Full Text Available Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume. We used amplified fragment length polymorphism (AFLP and methylation-sensitive amplified polymorphism (MSAP techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80% was detected in 96 accessions of P. mume. And the relative hemi-methylation level (15.77% was higher than the relative full methylation level (14.03%. The epigenetic diversity (I∗ = 0.575, h∗ = 0.393 was higher than the genetic diversity (I = 0.484, h = 0.319. The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.
Ma, Kaifeng; Sun, Lidan; Cheng, Tangren; Pan, Huitang; Wang, Jia; Zhang, Qixiang
2018-01-01
Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume . We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80%) was detected in 96 accessions of P . mume . And the relative hemi-methylation level (15.77%) was higher than the relative full methylation level (14.03%). The epigenetic diversity ( I ∗ = 0.575, h ∗ = 0.393) was higher than the genetic diversity ( I = 0.484, h = 0.319). The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.
DEFF Research Database (Denmark)
Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke
Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...
DEFF Research Database (Denmark)
Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage
2012-01-01
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...
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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.
San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre
2017-10-01
The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
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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.
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Carolina L. A. Da Silva
2018-04-01
Full Text Available We investigated (1 the relationship between the estimated breeding values (EBVs for litter traits at birth and ovulation rate (OR, average corpora luteal weight, uterine length and embryonic survival and development traits in gilts at 35 days of pregnancy by linear regression, (2 the genetic variance of OR, average corpora lutea (CL weight, uterine length and embryonic survival and development traits at 35 days of pregnancy, and (3 the genetic correlations between these traits. Landrace (n = 86 and Yorkshire × Landrace (n = 304 gilts were inseminated and slaughtered at 35 days of pregnancy. OR was assessed by dissection of the CL on both ovaries. Individual CL was weighed and the average CL weight calculated. The number of embryos (total and vital were counted and the vital embryos were individually weighed for calculation of within litter average and standard deviation (SD of the embryo weight. Length of the uterine implantation site of the vital embryos was measured and the average per gilt calculated. Results suggests that increasing the EBV for total number of piglets born would proportionally increase OR and number of embryos, while decreasing the average CL weight. On the contrary, increasing the EBV for average piglet birth weight and for within litter birth weight standard deviation would increase the average CL weight. There was no relationship between the EBVs for BW and for BWSD and vital embryonic weight at 35 days of pregnancy. OR, average CL weight, number of embryos, average weight and implantation length of the vital embryos had all moderate to high heritabilities, ranging from 0.36 (±0.18 to 0.70 (±0.17. Thus, results indicate that there is ample genetic variation in OR, average CL weight and embryonic development traits. This knowledge could be used to optimize the balance between selection for litter size, average piglets birth weight and within litter birth weight uniformity.
Influence of Family Structure on Variance Decomposition
DEFF Research Database (Denmark)
Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter
Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...
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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
Siren, J; Ovaskainen, O; Merilä, J
2017-10-01
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.
Downside Variance Risk Premium
Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric
2015-01-01
We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...
Validation of consistency of Mendelian sampling variance.
Tyrisevä, A-M; Fikse, W F; Mäntysaari, E A; Jakobsen, J; Aamand, G P; Dürr, J; Lidauer, M H
2018-03-01
Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating within-year genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic
MCNP variance reduction overview
International Nuclear Information System (INIS)
Hendricks, J.S.; Booth, T.E.
1985-01-01
The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code
Nonlinear Epigenetic Variance: Review and Simulations
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…
Estimation of measurement variances
International Nuclear Information System (INIS)
Anon.
1981-01-01
In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time
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.
Estimation of measurement variances
International Nuclear Information System (INIS)
Jaech, J.L.
1984-01-01
The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented
International Nuclear Information System (INIS)
Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.
2011-01-01
Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic
DEFF Research Database (Denmark)
Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander
2013-01-01
of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...
Restricted Variance Interaction Effects
DEFF Research Database (Denmark)
Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.
2018-01-01
Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...
Local variances in biomonitoring
International Nuclear Information System (INIS)
Wolterbeek, H.Th; Verburg, T.G.
2001-01-01
The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)
Local variances in biomonitoring
International Nuclear Information System (INIS)
Wolterbeek, H.T.
1999-01-01
The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)
Spectral Ambiguity of Allan Variance
Greenhall, C. A.
1996-01-01
We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.
Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.
Diaz, S Anaid; Viney, Mark
2014-06-01
Organisms live in heterogeneous environments, so strategies that maximze fitness in such environments will evolve. Variation in traits is important because it is the raw material on which natural selection acts during evolution. Phenotypic variation is usually thought to be due to genetic variation and/or environmentally induced effects. Therefore, genetically identical individuals in a constant environment should have invariant traits. Clearly, genetically identical individuals do differ phenotypically, usually thought to be due to stochastic processes. It is now becoming clear, especially from studies of unicellular species, that phenotypic variance among genetically identical individuals in a constant environment can be genetically controlled and that therefore, in principle, this can be subject to selection. However, there has been little investigation of these phenomena in multicellular species. Here, we have studied the mean lifetime fecundity (thus a trait likely to be relevant to reproductive success), and variance in lifetime fecundity, in recently-wild isolates of the model nematode Caenorhabditis elegans. We found that these genotypes differed in their variance in lifetime fecundity: some had high variance in fecundity, others very low variance. We find that this variance in lifetime fecundity was negatively related to the mean lifetime fecundity of the lines, and that the variance of the lines was positively correlated between environments. We suggest that the variance in lifetime fecundity may be a bet-hedging strategy used by this species.
Introduction to variance estimation
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...
Directory of Open Access Journals (Sweden)
Antonia Kécya França Moita
2010-07-01
Full Text Available Registros de produção de leite de 754 búfalas da raça Murrah foram utilizados com o objetivo de avaliar o efeito da heterogeneidade de variâncias na avaliação genética. Os componentes de covariância foram estimados pelo método da máxima verossimilhança restrita utilizando-se quatro modelos bicaracterísticos, considerando, como efeitos fixos, estação de parto e rebanho-ano de parto, e idade da vaca como covariável (efeito linear e quadrático. Os quatro modelos utilizados foram: modelo aditivo; modelo de repetibilidade; modelo aditivo com inclusão interação reprodutor x rebanho-ano; modelo de repetibilidade com inclusão da interação reprodutor x rebanho-ano. Os rebanhos foram classificados em duas classes de desvio-padrão fenotípico para produção de leite e análises bicaracterísticas foram realizadas considerando cada classe de desvio-padrão como característica diferente. Foi conduzida também uma análise unicaracterística desconsiderando as classes de desvio-padrão fenotípico, incluindo o efeito da interação reprodutor x rebanho-ano. As estimativas de componentes de variância genética aditiva foram maiores na classe de alto desvio-padrão, comparadas às de baixo desvio-padrão. A maioria dos animais selecionados nos arquivos sem estratificação foi selecionada para alto desvio-padrão. Apesar do aumento nas variâncias aditivas e do erro nas de classes de alto desvio-padrão, suas herdabilidades foram menores, com exceção do modelo 2, cujo herdabilidade foi maior para a classe de alto desvio-padrão. Quando rebanhos são classificados em alto e baixo desvio-padrão fenotípico e a produção de leite nas diferentes classes é avaliada em modelo multicaracterística, a avaliação genética considera a heterogeneidade de variâncias entre rebanhos.Milk yield records of 754 Murrah female buffaloes were used to evaluate the effects of heterogeneity of variance among herds on genetic evaluation. The
Comparison of variance estimators for metaanalysis of instrumental variable estimates
Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.
2016-01-01
Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two
A study of heterogeneity of environmental variance for slaughter weight in pigs
DEFF Research Database (Denmark)
Ibánez-Escriche, N; Varona, L; Sorensen, D
2008-01-01
This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...
Approximation errors during variance propagation
International Nuclear Information System (INIS)
Dinsmore, Stephen
1986-01-01
Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given
Phenotypic variance explained by local ancestry in admixed African Americans.
Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N
2015-01-01
We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.
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
Markov bridges, bisection and variance reduction
DEFF Research Database (Denmark)
Asmussen, Søren; Hobolth, Asger
. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...
Means and Variances without Calculus
Kinney, John J.
2005-01-01
This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.
The Genealogical Consequences of Fecundity Variance Polymorphism
Taylor, Jesse E.
2009-01-01
The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628
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.
Modelling volatility by variance decomposition
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...
Gini estimation under infinite variance
A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)
2018-01-01
textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient
Genetic marker effects and type of inheritance are estimated with poor precision when minor marker allele frequencies are low. A stable composite population (MARC III) was subjected to marker assisted selection for multiple years to equalize specific marker frequencies to 1) estimate effect size an...
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.
Variance decomposition in stochastic simulators.
Le Maître, O P; Knio, O M; Moraes, A
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maître, O. P.; Knio, O. M.; Moraes, A.
2015-06-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Energy Technology Data Exchange (ETDEWEB)
Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro
2015-01-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Li, Yang; Pirvu, Traian A
2011-01-01
This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.
Molecular variance of the Tunisian almond germplasm assessed by ...
African Journals Online (AJOL)
The genetic variance analysis of 82 almond (Prunus dulcis Mill.) genotypes was performed using ten genomic simple sequence repeats (SSRs). A total of 50 genotypes from Tunisia including local landraces identified while prospecting the different sites of Bizerte and Sidi Bouzid (Northern and central parts) which are the ...
Confidence Interval Approximation For Treatment Variance In ...
African Journals Online (AJOL)
In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...
International Nuclear Information System (INIS)
Hubitschek, H.E.
1975-01-01
Progress is reported on the following research projects: genetic effects of high LET radiations; genetic regulation, alteration, and repair; chromosome replication and the division cycle of Escherichia coli; effects of radioisotope decay in the DNA of microorganisms; initiation and termination of DNA replication in Bacillus subtilis; mutagenesis in mouse myeloma cells; lethal and mutagenic effects of near-uv radiation; effect of 8-methoxypsoralen on photodynamic lethality and mutagenicity in Escherichia coli; DNA repair of the lethal effects of far-uv; and near uv irradiation of bacterial cells
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...
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.
Speed Variance and Its Influence on Accidents.
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…
Variance function estimation for immunoassays
International Nuclear Information System (INIS)
Raab, G.M.; Thompson, R.; McKenzie, I.
1980-01-01
A computer program is described which implements a recently described, modified likelihood method of determining an appropriate weighting function to use when fitting immunoassay dose-response curves. The relationship between the variance of the response and its mean value is assumed to have an exponential form, and the best fit to this model is determined from the within-set variability of many small sets of repeated measurements. The program estimates the parameter of the exponential function with its estimated standard error, and tests the fit of the experimental data to the proposed model. Output options include a list of the actual and fitted standard deviation of the set of responses, a plot of actual and fitted standard deviation against the mean response, and an ordered list of the 10 sets of data with the largest ratios of actual to fitted standard deviation. The program has been designed for a laboratory user without computing or statistical expertise. The test-of-fit has proved valuable for identifying outlying responses, which may be excluded from further analysis by being set to negative values in the input file. (Auth.)
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
Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.
Nelson, Ronald M; Pettersson, Mats E; Li, Xidan; Carlborg, Örjan
2013-01-01
Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.
Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances
Deng, Wei Q; Asma, Senay; Paré, Guillaume
2014-01-01
Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533
A class of multi-period semi-variance portfolio for petroleum exploration and development
Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei
2012-10-01
Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.
Efficient Cardinality/Mean-Variance Portfolios
Brito, R. Pedro; Vicente, Luís Nunes
2014-01-01
International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...
The phenotypic variance gradient - a novel concept.
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.
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
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
Correlations between genetic variance and adiposity measures, and ...
Indian Academy of Sciences (India)
justed and adjusted for the covariates (P = 0.006 in adjusted model). In multiple logistic regression .... of the World Health Organization (WHO Expert Consul- tation 2004) and the ...... sity in urban Hanoi, Vietnam. Asia. Pac. J. Clin. Nutr. 18, 234 ...
(Co) variance Components and Genetic Parameter Estimates for Re
African Journals Online (AJOL)
Mapula
The magnitude of heritability estimates obtained in the current study ... traits were recently introduced to supplement progeny testing programmes or for usage as sole source of ..... VCE-5 User's Guide and Reference Manual Version 5.1.
Least-squares variance component estimation
Teunissen, P.J.G.; Amiri-Simkooei, A.R.
2007-01-01
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight
Expected Stock Returns and Variance Risk Premia
DEFF Research Database (Denmark)
Bollerslev, Tim; Zhou, Hao
risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...
Variance estimation for generalized Cavalieri estimators
Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen
2011-01-01
The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.
Portfolio optimization with mean-variance model
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.
Yeaman, Sam; Jarvis, Andy
2006-01-01
Genetic variation is of fundamental importance to biological evolution, yet we still know very little about how it is maintained in nature. Because many species inhabit heterogeneous environments and have pronounced local adaptations, gene flow between differently adapted populations may be a persistent source of genetic variation within populations. If this migration–selection balance is biologically important then there should be strong correlations between genetic variance within populations and the amount of heterogeneity in the environment surrounding them. Here, we use data from a long-term study of 142 populations of lodgepole pine (Pinus contorta) to compare levels of genetic variation in growth response with measures of climatic heterogeneity in the surrounding region. We find that regional heterogeneity explains at least 20% of the variation in genetic variance, suggesting that gene flow and heterogeneous selection may play an important role in maintaining the high levels of genetic variation found within natural populations. PMID:16769628
Portfolio optimization using median-variance approach
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.
Grammatical and lexical variance in English
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.
A Mean variance analysis of arbitrage portfolios
Fang, Shuhong
2007-03-01
Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.
Dynamic Mean-Variance Asset Allocation
Basak, Suleyman; Chabakauri, Georgy
2009-01-01
Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...
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.
Integrating Variances into an Analytical Database
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.
Decomposition of Variance for Spatial Cox Processes.
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
2013-03-01
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.
Variance in binary stellar population synthesis
Breivik, Katelyn; Larson, Shane L.
2016-03-01
In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.
Estimating quadratic variation using realized variance
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2002-01-01
with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....
2010-07-01
...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...
78 FR 14122 - Revocation of Permanent Variances
2013-03-04
... Douglas Fir planking had to have at least a 1,900 fiber stress and 1,900,000 modulus of elasticity, while the Yellow Pine planking had to have at least 2,500 fiber stress and 2,000,000 modulus of elasticity... the permanent variances, and affected employees, to submit written data, views, and arguments...
Variance Risk Premia on Stocks and Bonds
DEFF Research Database (Denmark)
Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea
Investors in fixed income markets are willing to pay a very large premium to be hedged against shocks in expected volatility and the size of this premium can be studied through variance swaps. Using thirty years of option and high-frequency data, we document the following novel stylized facts...
Biological Variance in Agricultural Products. Theoretical Considerations
Tijskens, L.M.M.; Konopacki, P.
2003-01-01
The food that we eat is uniform neither in shape or appearance nor in internal composition or content. Since technology became increasingly important, the presence of biological variance in our food became more and more of a nuisance. Techniques and procedures (statistical, technical) were
Decomposition of variance for spatial Cox processes
DEFF Research Database (Denmark)
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...
Decomposition of variance for spatial Cox processes
DEFF Research Database (Denmark)
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
2013-01-01
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...
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...
Variance Swap Replication: Discrete or Continuous?
Directory of Open Access Journals (Sweden)
Fabien Le Floc’h
2018-02-01
Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.
Zero-intelligence realized variance estimation
Gatheral, J.; Oomen, R.C.A.
2010-01-01
Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and
Variance Reduction Techniques in Monte Carlo Methods
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
DEFF Research Database (Denmark)
Casas, Isabel; Mao, Xiuping; Veiga, Helena
This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...... time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil........ Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional...
R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.
Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil
2011-01-01
We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.
Realized Variance and Market Microstructure Noise
DEFF Research Database (Denmark)
Hansen, Peter R.; Lunde, Asger
2006-01-01
We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...
The Theory of Variances in Equilibrium Reconstruction
International Nuclear Information System (INIS)
Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren
2008-01-01
The theory of variances of equilibrium reconstruction is presented. It complements existing practices with information regarding what kind of plasma profiles can be reconstructed, how accurately, and what remains beyond the abilities of diagnostic systems. The σ-curves, introduced by the present theory, give a quantitative assessment of quality of effectiveness of diagnostic systems in constraining equilibrium reconstructions. The theory also suggests a method for aligning the accuracy of measurements of different physical nature
Fundamentals of exploratory analysis of variance
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.
Variance analysis refines overhead cost control.
Cooper, J C; Suver, J D
1992-02-01
Many healthcare organizations may not fully realize the benefits of standard cost accounting techniques because they fail to routinely report volume variances in their internal reports. If overhead allocation is routinely reported on internal reports, managers can determine whether billing remains current or lost charges occur. Healthcare organizations' use of standard costing techniques can lead to more realistic performance measurements and information system improvements that alert management to losses from unrecovered overhead in time for corrective action.
DEFF Research Database (Denmark)
Bekkevold, Dorte
2006-01-01
Estimates of Atlantic cod Gadus morhua reproductive success, determined using experimental spawning groups and genetic paternity assignment of offspring, showed that within-group variance in male size correlated positively with the degree of male mating skew, predicting a decrease in male reprodu...
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 individu...
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.)
Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans
Raju, C.; Vidya, R.
2016-06-01
In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.
Visual SLAM Using Variance Grid Maps
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
The value of travel time variance
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...
Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley
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
Journal of Genetics | Indian Academy of Sciences
Indian Academy of Sciences (India)
polygenes; additive genetic variance; epistasis; dominance; selection ... seem to run out of genetic variability even after many generations of directional selection. ... Conspicuous examples are the small number of loci that changed teosinte to ...
Variance-based Salt Body Reconstruction
Ovcharenko, Oleg
2017-05-26
Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.
A zero-variance-based scheme for variance reduction in Monte Carlo criticality
Energy Technology Data Exchange (ETDEWEB)
Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)
2006-07-01
A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)
A zero-variance-based scheme for variance reduction in Monte Carlo criticality
International Nuclear Information System (INIS)
Christoforou, S.; Hoogenboom, J. E.
2006-01-01
A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)
Genetic variability, heritability and genetic advance of quantitative ...
African Journals Online (AJOL)
ONOS
2010-05-10
May 10, 2010 ... coefficient of variation; h2, heritability; GA, genetic advance;. EMS, ethyl methane ... The analysis of variance (ANOVA) revealed the significance degree among the ... fullest extent. The estimates of range, phenotypic and.
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.
Analysis of Variance in Statistical Image Processing
Kurz, Ludwik; Hafed Benteftifa, M.
1997-04-01
A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
Variance Risk Premia on Stocks and Bonds
DEFF Research Database (Denmark)
Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea
We study equity (EVRP) and Treasury variance risk premia (TVRP) jointly and document a number of findings: First, relative to their volatility, TVRP are comparable in magnitude to EVRP. Second, while there is mild positive co-movement between EVRP and TVRP unconditionally, time series estimates...... equity returns for horizons up to 6-months, long maturity TVRP contain robust information for long run equity returns. Finally, exploiting the dynamics of real and nominal Treasuries we document that short maturity break-even rates are a power determinant of the joint dynamics of EVRP, TVRP and their co-movement...... of correlation display distinct spikes in both directions and have been notably volatile since the financial crisis. Third $(i)$ short maturity TVRP predict excess returns on short maturity bonds; $(ii)$ long maturity TVRP and EVRP predict excess returns on long maturity bonds; and $(iii)$ while EVRP predict...
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....
Hybrid biasing approaches for global variance reduction
International Nuclear Information System (INIS)
Wu, Zeyun; Abdel-Khalik, Hany S.
2013-01-01
A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.
The contribution of the mitochondrial genome to sex-specific fitness variance.
Smith, Shane R T; Connallon, Tim
2017-05-01
Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.
Dazard, Jean-Eudes; Rao, J Sunil
2012-07-01
The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.
Gene interactions and genetics of blast resistance and yield ...
Indian Academy of Sciences (India)
2014-08-11
Aug 11, 2014 ... of chemical measures for the control and management of blast, which are not .... tion of genetic components of variation, epistasis model and gene effects in two .... and environmental variance is estimated from mean variance.
76 FR 78698 - Proposed Revocation of Permanent Variances
2011-12-19
... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...
The effect of sex on the mean and variance of fitness in facultatively sexual rotifers.
Becks, L; Agrawal, A F
2011-03-01
The evolution of sex is a classic problem in evolutionary biology. While this topic has been the focus of much theoretical work, there is a serious dearth of empirical data. A simple yet fundamental question is how sex affects the mean and variance in fitness. Despite its importance to the theory, this type of data is available for only a handful of taxa. Here, we report two experiments in which we measure the effect of sex on the mean and variance in fitness in the monogonont rotifer, Brachionus calyciflorus. Compared to asexually derived offspring, we find that sexual offspring have lower mean fitness and less genetic variance in fitness. These results indicate that, at least in the laboratory, there are both short- and long-term disadvantages associated with sexual reproduction. We briefly review the other available data and highlight the need for future work. © 2010 The Authors. Journal of Evolutionary Biology © 2010 European Society For Evolutionary Biology.
DEFF Research Database (Denmark)
Bilde, T.; Friberg, U.; Maklakov, A.A.
2008-01-01
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...
Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.
Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S
2018-02-15
Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.
The Distribution of the Sample Minimum-Variance Frontier
Raymond Kan; Daniel R. Smith
2008-01-01
In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...
Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability
DEFF Research Database (Denmark)
Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco
We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....
Lebigre, Christophe; Arcese, Peter; Reid, Jane M
2013-07-01
Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased
Variance components 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.
Gene set analysis using variance component tests.
Huang, Yen-Tsung; Lin, Xihong
2013-06-28
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. 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). 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.
Regional sensitivity analysis using revised mean and variance ratio functions
International Nuclear Information System (INIS)
Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen
2014-01-01
The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure
Estimating the encounter rate variance in distance sampling
Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.
2009-01-01
The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.
Variance swap payoffs, risk premia and extreme market conditions
DEFF Research Database (Denmark)
Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco
This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....
Towards a mathematical foundation of minimum-variance theory
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)
2002-08-30
The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)
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...
RR-Interval variance of electrocardiogram for atrial fibrillation detection
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.
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.
Network Structure and Biased Variance Estimation in Respondent Driven Sampling.
Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J
2015-01-01
This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.
Multiperiod Mean-Variance Portfolio Optimization via Market Cloning
International Nuclear Information System (INIS)
Ankirchner, Stefan; Dermoune, Azzouz
2011-01-01
The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.
Discrete and continuous time dynamic mean-variance analysis
Reiss, Ariane
1999-01-01
Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...
Discrete time and continuous time dynamic mean-variance analysis
Reiss, Ariane
1999-01-01
Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...
ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE
Abdurakhman, Abdurakhman
2008-01-01
Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...
Capturing option anomalies with a variance-dependent pricing kernel
Christoffersen, P.; Heston, S.; Jacobs, K.
2013-01-01
We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is
Realized range-based estimation of integrated variance
DEFF Research Database (Denmark)
Christensen, Kim; Podolskij, Mark
2007-01-01
We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...
Diagnostic checking in linear processes with infinit variance
Krämer, Walter; Runde, Ralf
1998-01-01
We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.
Evaluation of Mean and Variance Integrals without Integration
Joarder, A. H.; Omar, M. H.
2007-01-01
The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…
Adjustment of heterogenous variances and a calving year effect in ...
African Journals Online (AJOL)
Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models.
Direct encoding of orientation variance in the visual system.
Norman, Liam J; Heywood, Charles A; Kentridge, Robert W
2015-01-01
Our perception of regional irregularity, an example of which is orientation variance, seems effortless when we view two patches of texture that differ in this attribute. Little is understood, however, of how the visual system encodes a regional statistic like orientation variance, but there is some evidence to suggest that it is directly encoded by populations of neurons tuned broadly to high or low levels. The present study shows that selective adaptation to low or high levels of variance results in a perceptual aftereffect that shifts the perceived level of variance of a subsequently viewed texture in the direction away from that of the adapting stimulus (Experiments 1 and 2). Importantly, the effect is durable across changes in mean orientation, suggesting that the encoding of orientation variance is independent of global first moment orientation statistics (i.e., mean orientation). In Experiment 3 it was shown that the variance-specific aftereffect did not show signs of being encoded in a spatiotopic reference frame, similar to the equivalent aftereffect of adaptation to the first moment orientation statistic (the tilt aftereffect), which is represented in the primary visual cortex and exists only in retinotopic coordinates. Experiment 4 shows that a neuropsychological patient with damage to ventral areas of the cortex but spared intact early areas retains sensitivity to orientation variance. Together these results suggest that orientation variance is encoded directly by the visual system and possibly at an early cortical stage.
Beyond the Mean: Sensitivities of the Variance of Population Growth.
Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad
2013-03-01
Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.
On the Endogeneity of the Mean-Variance Efficient Frontier.
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…
42 CFR 456.522 - Content of request for variance.
2010-10-01
... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...
29 CFR 1905.5 - Effect of variances.
2010-07-01
...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...
29 CFR 1904.38 - Variances from the recordkeeping rule.
2010-07-01
..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...
Gender Variance and Educational Psychology: Implications for Practice
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…
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.
Genet and tic vari d seed iability yield t oc y and h traits i cciden ...
African Journals Online (AJOL)
SAM
between two variables; δ2x is the genotypic or phenotypic variance of the variable x, δ2y is the genotypic or phenotypic variance of the variable yield y. .... var = genotypic variance; Env var = environmental variance; PCV = phenotypic coefficient of variability; GCV = genotypic coefficient of variability; Gen adv% = genetic ...
Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D
2013-07-03
Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.
DEFF Research Database (Denmark)
Chown, Steven L.; Jumbam, Keafon R.; Sørensen, Jesper Givskov
2009-01-01
used during assessments of critical thermal limits to activity. To date, the focus of work has almost exclusively been on the effects of rate variation on mean values of the critical limits. 2. If the rate of temperature change used in an experimental trial affects not only the trait mean but also its...... this is the case for critical thermal limits using a population of the model species Drosophila melanogaster and the invasive ant species Linepithema humile. 4. We found that effects of the different rates of temperature change are variable among traits and species. However, in general, different rates...... of temperature change resulted in different phenotypic variances and different estimates of heritability, presuming that genetic variance remains constant. We also found that different rates resulted in different conclusions regarding the responses of the species to acclimation, especially in the case of L...
Variance-based selection may explain general mating patterns in social insects.
Rueppell, Olav; Johnson, Nels; Rychtár, Jan
2008-06-23
Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.
Integrating mean and variance heterogeneities to identify differentially expressed genes.
Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen
2016-12-06
In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment
Felleki, M; Lee, D; Lee, Y; Gilmour, A R; Rönnegård, L
2012-12-01
The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being -0·52 for IRWLS and -0·62 in Sorensen & Waagepetersen (2003).
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
Variance computations for functional of absolute risk estimates.
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.
Estimating High-Frequency Based (Co-) Variances: A Unified Approach
DEFF Research Database (Denmark)
Voev, Valeri; Nolte, Ingmar
We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...
Genetic improvement of vegetables
International Nuclear Information System (INIS)
Jaramillo Vasquez, J.G.
2001-01-01
Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties
Capturing Option Anomalies with a Variance-Dependent Pricing Kernel
DEFF Research Database (Denmark)
Christoffersen, Peter; Heston, Steven; Jacobs, Kris
2013-01-01
We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....
Allowable variance set on left ventricular function parameter
International Nuclear Information System (INIS)
Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin
2010-01-01
Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)
Host nutrition alters the variance in parasite transmission potential.
Vale, Pedro F; Choisy, Marc; Little, Tom J
2013-04-23
The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.
Minimum variance Monte Carlo importance sampling with parametric dependence
International Nuclear Information System (INIS)
Ragheb, M.M.H.; Halton, J.; Maynard, C.W.
1981-01-01
An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de
Advanced methods of analysis variance on scenarios of nuclear prospective
International Nuclear Information System (INIS)
Blazquez, J.; Montalvo, C.; Balbas, M.; Garcia-Berrocal, A.
2011-01-01
Traditional techniques of propagation of variance are not very reliable, because there are uncertainties of 100% relative value, for this so use less conventional methods, such as Beta distribution, Fuzzy Logic and the Monte Carlo Method.
Some variance reduction methods for numerical stochastic homogenization.
Blanc, X; Le Bris, C; Legoll, F
2016-04-28
We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).
Variance Function Partially Linear Single-Index Models1.
Lian, Heng; Liang, Hua; Carroll, Raymond J
2015-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.
Variance estimation in the analysis of microarray data
Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.
2009-01-01
Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing
Röring, Johan
2017-01-01
Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...
ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER
SENGUPTA, Jati K.; PARK, Hyung S.
1994-01-01
The hypothesis that the skewness and asymmetry have no significant impact on the mean variance frontier is found to be strongly violated by monthly U.S. data over the period January 1965 through December 1974. This result raises serious doubts whether the common market portifolios such as SP 500, value weighted and equal weighted returns can serve as suitable proxies for meanvariance efficient portfolios in the CAPM framework. A new test for assessing the impact of skewness on the variance fr...
Towards the ultimate variance-conserving convection scheme
International Nuclear Information System (INIS)
Os, J.J.A.M. van; Uittenbogaard, R.E.
2004-01-01
In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287
Problems of variance reduction in the simulation of random variables
International Nuclear Information System (INIS)
Lessi, O.
1987-01-01
The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced
Cumulative prospect theory and mean variance analysis. A rigorous comparison
Hens, Thorsten; Mayer, Janos
2012-01-01
We compare asset allocations derived for cumulative prospect theory(CPT) based on two different methods: Maximizing CPT along the mean–variance efficient frontier and maximizing it without that restriction. We find that with normally distributed returns the difference is negligible. However, using standard asset allocation data of pension funds the difference is considerable. Moreover, with derivatives like call options the restriction to the mean-variance efficient frontier results in a siza...
Global Variance Risk Premium and Forex Return Predictability
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 ...
Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation
2008-12-01
slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that
Temperature variance study in Monte-Carlo photon transport theory
International Nuclear Information System (INIS)
Giorla, J.
1985-10-01
We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr
Mean-Variance Optimization in Markov Decision Processes
Mannor, Shie; Tsitsiklis, John N.
2011-01-01
We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.
The asymptotic variance of departures in critically loaded queues
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 +
Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''
International Nuclear Information System (INIS)
Nasseri, K.K.
1987-07-01
Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined
Variance estimation in the analysis of microarray data
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.
Why risk is not variance: an expository note.
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.
Approximate zero-variance Monte Carlo estimation of Markovian unreliability
International Nuclear Information System (INIS)
Delcoux, J.L.; Labeau, P.E.; Devooght, J.
1997-01-01
Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)
A versatile omnibus test for detecting mean and variance heterogeneity.
Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J
2014-01-01
Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.
Variance-based sensitivity indices for models with dependent inputs
International Nuclear Information System (INIS)
Mara, Thierry A.; Tarantola, Stefano
2012-01-01
Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.
Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'
International Nuclear Information System (INIS)
Nasseri, K.K.
1987-01-01
Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined
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
CMB-S4 and the hemispherical variance anomaly
O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.
2017-09-01
Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.
Estimation of the additive and dominance variances in SA Landrace ...
African Journals Online (AJOL)
NORRIS
South African Journal of Animal Science 2006, 36 (4) ... Fuerst (1996) simulated a genetic model with different levels of additive, dominance and additive by additive genetic effects to .... However, a simulation study by Norris et al. (2002) ...
How does variance in fertility change over the demographic transition?
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).
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.
A family-based joint test for mean and variance heterogeneity for quantitative traits.
Cao, Ying; Maxwell, Taylor J; Wei, Peng
2015-01-01
Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.
Impact of Damping Uncertainty on SEA Model Response Variance
Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand
2010-01-01
Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.
A new variance stabilizing transformation for gene expression data analysis.
Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor
2013-12-01
In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.
Pricing perpetual American options under multiscale stochastic elasticity of variance
International Nuclear Information System (INIS)
Yoon, Ji-Hun
2015-01-01
Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk
Monte Carlo variance reduction approaches for non-Boltzmann tallies
International Nuclear Information System (INIS)
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed
The mean and variance of phylogenetic diversity under rarefaction.
Nipperess, David A; Matsen, Frederick A
2013-06-01
Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.
Variance estimation for sensitivity analysis of poverty and inequality measures
Directory of Open Access Journals (Sweden)
Christian Dudel
2017-04-01
Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.
Studying Variance in the Galactic Ultra-compact Binary Population
Larson, Shane; Breivik, Katelyn
2017-01-01
In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.
Variance of a product with application to uranium estimation
International Nuclear Information System (INIS)
Lowe, V.W.; Waterman, M.S.
1976-01-01
The U in a container can either be determined directly by NDA or by estimating the weight of material in the container and the concentration of U in this material. It is important to examine the statistical properties of estimating the amount of U by multiplying the estimates of weight and concentration. The variance of the product determines the accuracy of the estimate of the amount of uranium. This paper examines the properties of estimates of the variance of the product of two random variables
Levine's guide to SPSS for analysis of variance
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
Variance squeezing and entanglement of the XX central spin model
International Nuclear Information System (INIS)
El-Orany, Faisal A A; Abdalla, M Sebawe
2011-01-01
In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.
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....
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.
Age-related variation in genetic control of height growth in Douglas-fir.
Namkoong, G; Usanis, R A; Silen, R R
1972-01-01
The development of genetic variances in height growth of Douglas-fir over a 53-year period is analyzed and found to fall into three periods. In the juvenile period, variances in environmental error increase logarithmically, genetic variance within populations exists at moderate levels, and variance among populations is low but increasing. In the early reproductive period, the response to environmental sources of error variance is restricted, genetic variance within populations disappears, and populational differences strongly emerge but do not increase as expected. In the later period, environmental error again increases rapidly, but genetic variance within populations does not reappear and population differences are maintained at about the same level as established in the early reproductive period. The change between the juvenile and early reproductive periods is perhaps associated with the onset of ecological dominance and significant allocations of energy to reproduction.
Energy Technology Data Exchange (ETDEWEB)
Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)
2011-07-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
International Nuclear Information System (INIS)
Christoforou, Stavros; Hoogenboom, J. Eduard
2011-01-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
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...
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
2014-01-01
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...
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...
Analysis of Variance: What Is Your Statistical Software Actually Doing?
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…
Cumulative Prospect Theory, Option Returns, and the Variance Premium
Baele, Lieven; Driessen, Joost; Ebert, Sebastian; Londono Yarce, J.M.; Spalt, Oliver
The variance premium and the pricing of out-of-the-money (OTM) equity index options are major challenges to standard asset pricing models. We develop a tractable equilibrium model with Cumulative Prospect Theory (CPT) preferences that can overcome both challenges. The key insight is that the
Hydrograph variances over different timescales in hydropower production networks
Zmijewski, Nicholas; Wörman, Anders
2016-08-01
The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of white noise) as a result of current production objectives.
Gravity interpretation of dipping faults using the variance analysis method
International Nuclear Information System (INIS)
Essa, Khalid S
2013-01-01
A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)
Bounds for Tail Probabilities of the Sample Variance
Directory of Open Access Journals (Sweden)
Van Zuijlen M
2009-01-01
Full Text Available We provide bounds for tail probabilities of the sample variance. The bounds are expressed in terms of Hoeffding functions and are the sharpest known. They are designed having in mind applications in auditing as well as in processing data related to environment.
Robust estimation of the noise variance from background MR data
Sijbers, J.; Den Dekker, A.J.; Poot, D.; Bos, R.; Verhoye, M.; Van Camp, N.; Van der Linden, A.
2006-01-01
In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust, and easy to use method is presented based on maximum
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...
Computing the Expected Value and Variance of Geometric Measures
DEFF Research Database (Denmark)
Staals, Frank; Tsirogiannis, Constantinos
2017-01-01
distance (MPD), the squared Euclidean distance from the centroid, and the diameter of the minimum enclosing disk. We also describe an efficient (1-e)-approximation algorithm for computing the mean and variance of the mean pairwise distance. We implemented three of our algorithms and we show that our...
Estimation of the additive and dominance variances in South African ...
African Journals Online (AJOL)
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 ...
A note on minimum-variance theory and beyond
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)
2004-04-30
We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.
A Visual Model for the Variance and Standard Deviation
Orris, J. B.
2011-01-01
This paper shows how the variance and standard deviation can be represented graphically by looking at each squared deviation as a graphical object--in particular, as a square. A series of displays show how the standard deviation is the size of the average square.
Multidimensional adaptive testing with a minimum error-variance criterion
van der Linden, Willem J.
1997-01-01
The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple
Asymptotics of variance of the lattice point count
Czech Academy of Sciences Publication Activity Database
Janáček, Jiří
2008-01-01
Roč. 58, č. 3 (2008), s. 751-758 ISSN 0011-4642 R&D Projects: GA AV ČR(CZ) IAA100110502 Institutional research plan: CEZ:AV0Z50110509 Keywords : point lattice * variance Subject RIV: BA - General Mathematics Impact factor: 0.210, year: 2008
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...
Estimates of variance components for postweaning feed intake and ...
African Journals Online (AJOL)
Mike
2013-03-09
Mar 9, 2013 ... transformation of RFIp and RDGp to z-scores (mean = 0.0, variance = 1.0) and then ... generation pedigree (n = 9 653) used for this analysis. ..... Nkrumah, J.D., Basarab, J.A., Wang, Z., Li, C., Price, M.A., Okine, E.K., Crews Jr., ...
An observation on the variance of a predicted response in ...
African Journals Online (AJOL)
... these properties and computational simplicity. To avoid over fitting, along with the obvious advantage of having a simpler equation, it is shown that the addition of a variable to a regression equation does not reduce the variance of a predicted response. Key words: Linear regression; Partitioned matrix; Predicted response ...
An entropy approach to size and variance heterogeneity
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
The Threat of Common Method Variance Bias to Theory Building
Reio, Thomas G., Jr.
2010-01-01
The need for more theory building scholarship remains one of the pressing issues in the field of HRD. Researchers can employ quantitative, qualitative, and/or mixed methods to support vital theory-building efforts, understanding however that each approach has its limitations. The purpose of this article is to explore common method variance bias as…
Variance in parametric images: direct estimation from parametric projections
International Nuclear Information System (INIS)
Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.
2000-01-01
Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)
40 CFR 268.44 - Variance from a treatment standard.
2010-07-01
... complete petition may be requested as needed to send to affected states and Regional Offices. (e) The... provide an opportunity for public comment. The final decision on a variance from a treatment standard will... than) the concentrations necessary to minimize short- and long-term threats to human health and the...
Application of effective variance method for contamination monitor calibration
International Nuclear Information System (INIS)
Goncalez, O.L.; Freitas, I.S.M. de.
1990-01-01
In this report, the calibration of a thin window Geiger-Muller type monitor for alpha superficial contamination is presented. The calibration curve is obtained by the method of the least-squares fitting with effective variance. The method and the approach for the calculation are briefly discussed. (author)
The VIX, the Variance Premium, and Expected Returns
DEFF Research Database (Denmark)
Osterrieder, Daniela Maria; Ventosa-Santaulària, Daniel; Vera-Valdés, Eduardo
2018-01-01
. These problems are eliminated if risk is captured by the variance premium (VP) instead; it is unobservable, however. We propose a 2SLS estimator that produces consistent estimates without observing the VP. Using this method, we find a positive risk–return trade-off and long-run return predictability. Our...
Some asymptotic theory for variance function smoothing | Kibua ...
African Journals Online (AJOL)
Simple selection of the smoothing parameter is suggested. Both homoscedastic and heteroscedastic regression models are considered. Keywords: Asymptotic, Smoothing, Kernel, Bandwidth, Bias, Variance, Mean squared error, Homoscedastic, Heteroscedastic. > East African Journal of Statistics Vol. 1 (1) 2005: pp. 9-22 ...
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...
Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...
African Journals Online (AJOL)
Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...
A note on minimum-variance theory and beyond
International Nuclear Information System (INIS)
Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello
2004-01-01
We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons
Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.
Ritz, Christian; Van der Vliet, Leana
2009-09-01
The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.
Starting design for use in variance exchange algorithms | Iwundu ...
African Journals Online (AJOL)
A new method of constructing the initial design for use in variance exchange algorithms is presented. The method chooses support points to go into the design as measures of distances of the support points from the centre of the geometric region and of permutation-invariant sets. The initial design is as close as possible to ...
Decomposition of variance in terms of conditional means
Directory of Open Access Journals (Sweden)
Alessandro Figà Talamanca
2013-05-01
Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..
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...
Heterogeneity of variance and its implications on dairy cattle breeding
African Journals Online (AJOL)
Milk yield data (n = 12307) from 116 Holstein-Friesian herds were grouped into three production environments based on mean and standard deviation of herd 305-day milk yield and evaluated for within herd variation using univariate animal model procedures. Variance components were estimated by derivative free REML ...
Effects of Diversification of Assets on Mean and Variance | Jayeola ...
African Journals Online (AJOL)
Diversification is a means of minimizing risk and maximizing returns by investing in a variety of assets of the portfolio. This paper is written to determine the effects of diversification of three types of Assets; uncorrelated, perfectly correlated and perfectly negatively correlated assets on mean and variance. To go about this, ...
Perspective projection for variance pose face recognition from camera calibration
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.
On zero variance Monte Carlo path-stretching schemes
International Nuclear Information System (INIS)
Lux, I.
1983-01-01
A zero variance path-stretching biasing scheme proposed for a special case by Dwivedi is derived in full generality. The procedure turns out to be the generalization of the exponential transform. It is shown that the biased game can be interpreted as an analog simulation procedure, thus saving some computational effort in comparison with the corresponding nonanalog game
A mean-variance frontier in discrete and continuous time
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
Hedging with stock index futures: downside risk versus the variance
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
The variance quadtree algorithm: use for spatial sampling design
Minasny, B.; McBratney, A.B.; Walvoort, D.J.J.
2007-01-01
Spatial sampling schemes are mainly developed to determine sampling locations that can cover the variation of environmental properties in the area of interest. Here we proposed the variance quadtree algorithm for sampling in an area with prior information represented as ancillary or secondary
Properties of realized variance under alternative sampling schemes
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
Variance component and heritability estimates of early growth traits ...
African Journals Online (AJOL)
as selection criteria for meat production in sheep (Anon, 1970; Olson et ai., 1976;. Lasslo et ai., 1985; Badenhorst et ai., 1991). If these traits are to be included in a breeding programme, accurate estimates of breeding values will be needed to optimize selection programmes. This requires a knowledge of variance and co-.
Variances in consumers prices of selected food Items among ...
African Journals Online (AJOL)
The study focused on the determination of variances among consumer prices of rice (local white), beans (white) and garri (yellow) in Watts, Okurikang and 8 Miles markets in southern zone of Cross River State. Completely randomized design was used to test the research hypothesis. Comparing the consumer prices of rice, ...
Age Differences in the Variance of Personality Characteristics
Czech Academy of Sciences Publication Activity Database
Mottus, R.; Allik, J.; Hřebíčková, Martina; Kööts-Ausmees, L.; Realo, A.
2016-01-01
Roč. 30, č. 1 (2016), s. 4-11 ISSN 0890-2070 R&D Projects: GA ČR GA13-25656S Institutional support: RVO:68081740 Keywords : variance * individual differences * personality * five-factor model Subject RIV: AN - Psychology Impact factor: 3.707, year: 2016
Some Conceptual Deficiencies in "Developmental" Behavior Genetics.
Gottlieb, Gilbert
1995-01-01
Criticizes the application of the statistical procedures of the population-genetic approach within evolutionary biology to the study of psychological development. Argues that the application of the statistical methods of population genetics--primarily the analysis of variance--to the causes of psychological development is bound to result in a…
Variance in exposed perturbations impairs retention of visuomotor adaptation.
Canaveral, Cesar Augusto; Danion, Frédéric; Berrigan, Félix; Bernier, Pierre-Michel
2017-11-01
Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay. NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of
Variance risk premia in CO_2 markets: A political perspective
International Nuclear Information System (INIS)
Reckling, Dennis
2016-01-01
The European Commission discusses the change of free allocation plans to guarantee a stable market equilibrium. Selling over-allocated contracts effectively depreciates prices and negates the effect intended by the regulator to establish a stable price mechanism for CO_2 assets. Our paper investigates mispricing and allocation issues by quantitatively analyzing variance risk premia of CO_2 markets over the course of changing regimes (Phase I-III) for three different assets (European Union Allowances, Certified Emissions Reductions and European Reduction Units). The research paper gives recommendations to regulatory bodies in order to most effectively cap the overall carbon dioxide emissions. The analysis of an enriched dataset, comprising not only of additional CO_2 assets, but also containing data from the European Energy Exchange, shows that variance risk premia are equal to a sample average of 0.69 for European Union Allowances (EUA), 0.17 for Certified Emissions Reductions (CER) and 0.81 for European Reduction Units (ERU). We identify the existence of a common risk factor across different assets that justifies the presence of risk premia. Various policy implications with regards to gaining investors’ confidence in the market are being reviewed. Consequently, we recommend the implementation of a price collar approach to support stable prices for emission allowances. - Highlights: •Enriched dataset covering all three political phases of the CO_2 markets. •Clear policy implications for regulators to most effectively cap the overall CO_2 emissions pool. •Applying a cross-asset benchmark index for variance beta estimation. •CER contracts have been analyzed with respect to variance risk premia for the first time. •Increased forecasting accuracy for CO_2 asset returns by using variance risk premia.
Directory of Open Access Journals (Sweden)
Struchalin Maksim V
2012-01-01
Full Text Available Abstract Background Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010 developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. Results In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. Conclusions Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.
Who Is Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety
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…
Estimates of variance components for postweaning feed intake and ...
African Journals Online (AJOL)
Feed efficiency is of major economic importance in beef production. The objective of this work was to evaluate alternative measures of feed efficiency for use in genetic evaluation. To meet this objective, genetic parameters were estimated for the components of efficiency. These parameters were then used in multiple-trait ...
Sex versus asex: An analysis of the role of variance conversion.
Lewis-Pye, Andrew E M; Montalbán, Antonio
2017-04-01
The question as to why most complex organisms reproduce sexually remains a very active research area in evolutionary biology. Theories dating back to Weismann have suggested that the key may lie in the creation of increased variability in offspring, causing enhanced response to selection. Under appropriate conditions, selection is known to result in the generation of negative linkage disequilibrium, with the effect of recombination then being to increase genetic variance by reducing these negative associations between alleles. It has therefore been a matter of significant interest to understand precisely those conditions resulting in negative linkage disequilibrium, and to recognise also the conditions in which the corresponding increase in genetic variation will be advantageous. Here, we prove rigorous results for the multi-locus case, detailing the build up of negative linkage disequilibrium, and describing the long term effect on population fitness for models with and without bounds on fitness contributions from individual alleles. Under the assumption of large but finite bounds on fitness contributions from alleles, the non-linear nature of the effect of recombination on a population presents serious obstacles in finding the genetic composition of populations at equilibrium, and in establishing convergence to those equilibria. We describe techniques for analysing the long term behaviour of sexual and asexual populations for such models, and use these techniques to establish conditions resulting in higher fitnesses for sexually reproducing populations. Copyright © 2017 Elsevier Inc. All rights reserved.
Partitioning of genomic variance using prior biological information
DEFF Research Database (Denmark)
Edwards, Stefan McKinnon; Janss, Luc; Madsen, Per
2013-01-01
variants influence complex diseases. Despite the successes, the variants identified as being statistically significant have generally explained only a small fraction of the heritable component of the trait, the so-called problem of missing heritability. Insufficient modelling of the underlying genetic...... architecture may in part explain this missing heritability. Evidence collected across genome-wide association studies in human provides 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 the associated genetic variants are enriched for genes that are connected in biol ogical pathways or for likely functional effects on genes. These biological findings provide valuable insight for developing better genomic models. These are statistical models for predicting complex trait phenotypes on the basis...
Developments in statistical analysis in quantitative genetics
DEFF Research Database (Denmark)
Sorensen, Daniel
2009-01-01
of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...
Adaptation to Variance of Stimuli in Drosophila Larva Navigation
Wolk, Jason; Gepner, Ruben; Gershow, Marc
In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.
PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS
Directory of Open Access Journals (Sweden)
Daniel Menezes Cavalcante
2016-07-01
Full Text Available Portfolio optimization strategies are advocated as being able to allow the composition of stocks portfolios that provide returns above market benchmarks. This study aims to determine whether, in fact, portfolios based on the minimum variance strategy, optimized by the Modern Portfolio Theory, are able to achieve earnings above market benchmarks in Brazil. Time series of 36 securities traded on the BM&FBOVESPA have been analyzed in a long period of time (1999-2012, with sample windows of 12, 36, 60 and 120 monthly observations. The results indicated that the minimum variance portfolio performance is superior to market benchmarks (CDI and IBOVESPA in terms of return and risk-adjusted return, especially in medium and long-term investment horizons.
Compounding approach for univariate time series with nonstationary variances
Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich
2015-12-01
A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.
Variance inflation in high dimensional Support Vector Machines
DEFF Research Database (Denmark)
Abrahamsen, Trine Julie; Hansen, Lars Kai
2013-01-01
Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...
Robust LOD scores for variance component-based linkage analysis.
Blangero, J; Williams, J T; Almasy, L
2000-01-01
The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.
Response variance in functional maps: neural darwinism revisited.
Directory of Open Access Journals (Sweden)
Hirokazu Takahashi
Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.
Response variance in functional maps: neural darwinism revisited.
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.
Replica approach to mean-variance portfolio optimization
Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre
2016-12-01
We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r = N/T optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.
Variance reduction methods applied to deep-penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.
1984-01-01
All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course
Spatial analysis based on variance of moving window averages
Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J
2006-01-01
A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...
A mean-variance frontier in discrete and continuous time
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 is based on the solution for the frontier in discrete time. Using the same multiperiod framework as Li and Ng (2000), I provide an alternative derivation and an alternative formulation of the solu...
Efficient Scores, Variance Decompositions and Monte Carlo Swindles.
1984-08-28
to ;r Then a version .of Pythagoras ’ theorem gives the variance decomposition (6.1) varT var S var o(T-S) P P0 0 0 One way to see this is to note...complete sufficient statistics for (B, a) , and that the standard- ized residuals a(y - XB) 6 are ancillary. Basu’s sufficiency- ancillarity theorem
Variance-based sensitivity analysis for wastewater treatment plant modelling.
Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B
2014-02-01
Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.
The mean and variance of phylogenetic diversity under rarefaction
Nipperess, David A.; Matsen, Frederick A.
2013-01-01
Phylogenetic diversity (PD) depends on sampling intensity, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD. We have derived exact formulae for t...
On mean reward variance in semi-Markov processes
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2005-01-01
Roč. 62, č. 3 (2005), s. 387-397 ISSN 1432-2994 R&D Projects: GA ČR(CZ) GA402/05/0115; GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : Markov and semi-Markov processes with rewards * variance of cumulative reward * asymptotic behaviour Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.259, year: 2005
Mean-Variance Analysis in a Multiperiod Setting
Frauendorfer, Karl; Siede, Heiko
1997-01-01
Similar to the classical Markowitz approach it is possible to apply a mean-variance criterion to a multiperiod setting to obtain efficient portfolios. To represent the stochastic dynamic characteristics necessary for modelling returns a process of asset returns is discretized with respect to time and space and summarized in a scenario tree. The resulting optimization problem is solved by means of stochastic multistage programming. The optimal solutions show equivalent structural properties as...
Analytic solution to variance optimization with no short positions
Kondor, Imre; Papp, Gábor; Caccioli, Fabio
2017-12-01
We consider the variance portfolio optimization problem with a ban on short selling. We provide an analytical solution by means of the replica method for the case of a portfolio of independent, but not identically distributed, assets. We study the behavior of the solution as a function of the ratio r between the number N of assets and the length T of the time series of returns used to estimate risk. The no-short-selling constraint acts as an asymmetric \
Variance components and selection response for feather-pecking behavior in laying hens.
Su, G; Kjaer, J B; Sørensen, P
2005-01-01
Variance components and selection response for feather pecking behavior were studied by analyzing the data from a divergent selection experiment. An investigation indicated that a Box-Cox transformation with power lambda = -0.2 made the data approximately normally distributed and gave the best fit for the model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the investigated traits in both the low feather-pecking line (LP) and the high feather-pecking line (HP). Based on the mean of marginal posterior distribution, in the Box-Cox transformed scale, heritability for number of feather pecking bouts (FP bouts) was 0.174 in line LP and 0.139 in line HP. For number of feather-pecking pecks (FP pecks), heritability was 0.139 in line LP and 0.105 in line HP. No full-sib group effect and observation pen effect were found in the 2 traits. After 4 generations of selection, the total response for number of FP bouts in the transformed scale was 58 and 74% of the mean of the first generation in line LP and line HP, respectively. The total response for number of FP pecks was 47 and 46% of the mean of the first generation in line LP and line HP, respectively. The variance components and the realized selection response together suggest that genetic selection can be effective in minimizing FP behavior. This would be expected to reduce one of the major welfare problems in laying hens.
Genetic Variation in Schizophrenia Liability is Shared With Intellectual Ability and Brain Structure
Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Kahn, René S; Hulshoff Pol, Hilleke E
2016-01-01
BACKGROUND: Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying
Estimating Predictive Variance for Statistical Gas Distribution Modelling
International Nuclear Information System (INIS)
Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo
2009-01-01
Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.
Improved estimation of the variance in Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Hoogenboom, J. Eduard
2008-01-01
Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k eff results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k eff will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k eff are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)
Improved estimation of the variance in Monte Carlo criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)
2008-07-01
Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k{sub eff} results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k{sub eff} will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k{sub eff} are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)
A general transform for variance reduction in Monte Carlo simulations
International Nuclear Information System (INIS)
Becker, T.L.; Larsen, E.W.
2011-01-01
This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)
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.
Genetic Parameters of Common Wheat in Nepal
Bal Krishna Joshi; Dhruba Bahadur Thapa; Madan Raj Bhatta
2015-01-01
Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correla...
Genetics of zinc tolerance in Anthoxanthum odoratum and Agrostis tenuis
Energy Technology Data Exchange (ETDEWEB)
Gartside, D W; McNeilly, T
1974-01-01
The genetic control of zinc tolerance in the grass Anthoxanthum odoratum and Agrostis tenuis has been examined using both the pair cross technique and the diallele analysis procedure used by others. Evidence is presented that the genetic control of zinc tolerance in both species is dominant and directional with a high degree of additive genetic variance.
Litter size, fur quality and genetic analyses of American mink
DEFF Research Database (Denmark)
Thirstrup, Janne Pia
of the skin, have been analyzed. Both fur quality traits and litter size are complex traits underlying quantitative genetic variation. Methods for estimating genetic variance, spanning from pedigree information to the use of different genetic markers, have been utilized in order to gain knowledge about...
Individual differences in personality traits reflect structural variance in specific brain regions.
Gardini, Simona; Cloninger, C Robert; Venneri, Annalena
2009-06-30
Personality dimensions such as novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (PER) are said to be heritable, stable across time and dependent on genetic and neurobiological factors. Recently a better understanding of the relationship between personality traits and brain structures/systems has become possible due to advances in neuroimaging techniques. This Magnetic Resonance Imaging (MRI) study investigated if individual differences in these personality traits reflected structural variance in specific brain regions. A large sample of eighty five young adult participants completed the Three-dimensional Personality Questionnaire (TPQ) and had their brain imaged with MRI. A voxel-based correlation analysis was carried out between individuals' personality trait scores and grey matter volume values extracted from 3D brain scans. NS correlated positively with grey matter volume in frontal and posterior cingulate regions. HA showed a negative correlation with grey matter volume in orbito-frontal, occipital and parietal structures. RD was negatively correlated with grey matter volume in the caudate nucleus and in the rectal frontal gyrus. PER showed a positive correlation with grey matter volume in the precuneus, paracentral lobule and parahippocampal gyrus. These results indicate that individual differences in the main personality dimensions of NS, HA, RD and PER, may reflect structural variance in specific brain areas.
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.......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...
A proxy for variance in dense matching over homogeneous terrain
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
Estimation of noise-free variance to measure heterogeneity.
Directory of Open Access Journals (Sweden)
Tilo Winkler
Full Text Available Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV(2. The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CV(r(2 for comparison with our estimate of noise-free or 'true' heterogeneity (CV(t(2. We found that CV(t(2 was only 5.4% higher than CV(r2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13NN-saline injection. The mean CV(t(2 was 0.10 (range: 0.03-0.30, while the mean CV(2 including noise was 0.24 (range: 0.10-0.59. CV(t(2 was in average 41.5% of the CV(2 measured including noise (range: 17.8-71.2%. The reproducibility of CV(t(2 was evaluated using three repeated PET scans from five subjects. Individual CV(t(2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV(t(2 in PET scans, and may be useful for similar statistical problems in experimental data.
On the noise variance of a digital mammography system
International Nuclear Information System (INIS)
Burgess, Arthur
2004-01-01
A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel
Strong genetic overlap between executive functions and intelligence.
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 (c) 2016 APA, all rights reserved).
Soave, David; Sun, Lei
2017-09-01
We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Fringe biasing: A variance reduction technique for optically thick meshes
Energy Technology Data Exchange (ETDEWEB)
Smedley-Stevenson, R. P. [AWE PLC, Aldermaston Reading, Berkshire, RG7 4PR (United Kingdom)
2013-07-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
Fringe biasing: A variance reduction technique for optically thick meshes
International Nuclear Information System (INIS)
Smedley-Stevenson, R. P.
2013-01-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
An Empirical Temperature Variance Source Model in Heated Jets
Khavaran, Abbas; Bridges, James
2012-01-01
An acoustic analogy approach is implemented that models the sources of jet noise in heated jets. The equivalent sources of turbulent mixing noise are recognized as the differences between the fluctuating and Favre-averaged Reynolds stresses and enthalpy fluxes. While in a conventional acoustic analogy only Reynolds stress components are scrutinized for their noise generation properties, it is now accepted that a comprehensive source model should include the additional entropy source term. Following Goldstein s generalized acoustic analogy, the set of Euler equations are divided into two sets of equations that govern a non-radiating base flow plus its residual components. When the base flow is considered as a locally parallel mean flow, the residual equations may be rearranged to form an inhomogeneous third-order wave equation. A general solution is written subsequently using a Green s function method while all non-linear terms are treated as the equivalent sources of aerodynamic sound and are modeled accordingly. In a previous study, a specialized Reynolds-averaged Navier-Stokes (RANS) solver was implemented to compute the variance of thermal fluctuations that determine the enthalpy flux source strength. The main objective here is to present an empirical model capable of providing a reasonable estimate of the stagnation temperature variance in a jet. Such a model is parameterized as a function of the mean stagnation temperature gradient in the jet, and is evaluated using commonly available RANS solvers. The ensuing thermal source distribution is compared with measurements as well as computational result from a dedicated RANS solver that employs an enthalpy variance and dissipation rate model. Turbulent mixing noise predictions are presented for a wide range of jet temperature ratios from 1.0 to 3.20.
Double Minimum Variance Beamforming Method to Enhance Photoacoustic Imaging
Paridar, Roya; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza; Orooji, Mahdi
2018-01-01
One of the common algorithms used to reconstruct photoacoustic (PA) images is the non-adaptive Delay-and-Sum (DAS) beamformer. However, the quality of the reconstructed PA images obtained by DAS is not satisfying due to its high level of sidelobes and wide mainlobe. In contrast, adaptive beamformers, such as minimum variance (MV), result in an improved image compared to DAS. In this paper, a novel beamforming method, called Double MV (D-MV) is proposed to enhance the image quality compared to...
A Note on the Kinks at the Mean Variance Frontier
Vörös, J.; Kriens, J.; Strijbosch, L.W.G.
1997-01-01
In this paper the standard portfolio case with short sales restrictions is analyzed.Dybvig pointed out that if there is a kink at a risky portfolio on the efficient frontier, then the securities in this portfolio have equal expected return and the converse of this statement is false.For the existence of kinks at the efficient frontier the sufficient condition is given here and a new procedure is used to derive the efficient frontier, i.e. the characteristics of the mean variance frontier.
Variance reduction techniques in the simulation of Markov processes
International Nuclear Information System (INIS)
Lessi, O.
1987-01-01
We study a functional r of the stationary distribution of a homogeneous Markov chain. It is often difficult or impossible to perform the analytical calculation of r and so it is reasonable to estimate r by a simulation process. A consistent estimator r(n) of r is obtained with respect to a chain with a countable state space. Suitably modifying the estimator r(n) of r one obtains a new consistent estimator which has a smaller variance than r(n). The same is obtained in the case of finite state space
A guide to SPSS for analysis of variance
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
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...... 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...
A Fay-Herriot Model with Different Random Effect Variances
Czech Academy of Sciences Publication Activity Database
Hobza, Tomáš; Morales, D.; Herrador, M.; Esteban, M.D.
2011-01-01
Roč. 40, č. 5 (2011), s. 785-797 ISSN 0361-0926 R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : small area estimation * Fay-Herriot model * Linear mixed model * Labor Force Survey Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.274, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/hobza-a%20fay-herriot%20model%20with%20different%20random%20effect%20variances.pdf
Variational Variance Reduction for Monte Carlo Criticality Calculations
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Larsen, Edward W.
2001-01-01
A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions
Genetic adaptability of durum wheat to salinity level at germination ...
African Journals Online (AJOL)
Administrator
2011-05-23
May 23, 2011 ... Keys words: Durum wheat, genetic-adaptability, salinity level. ... tolerance of crop proves the first way to overcome the limitation of crops ... Analysis of variance using GLM procedures (SAS, 1990) were used ... Additive, dominance and environmental variance components were ..... Breeding for stability of.
Genetic diversity, classification and comparative study on the larval ...
African Journals Online (AJOL)
Genetic diversity, classification and comparative study on the larval phenotypic ... B. mori showed different performance based on larval phenotypic data. The analysis of variance regarding the studied traits showed that different strains have ...
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.
Parameter uncertainty effects on variance-based sensitivity analysis
International Nuclear Information System (INIS)
Yu, W.; Harris, T.J.
2009-01-01
In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used
Variance of indoor radon concentration: Major influencing factors
Energy Technology Data Exchange (ETDEWEB)
Yarmoshenko, I., E-mail: ivy@ecko.uran.ru [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Vasilyev, A.; Malinovsky, G. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Bossew, P. [German Federal Office for Radiation Protection (BfS), Berlin (Germany); Žunić, Z.S. [Institute of Nuclear Sciences “Vinca”, University of Belgrade (Serbia); Onischenko, A.; Zhukovsky, M. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation)
2016-01-15
Variance of radon concentration in dwelling atmosphere is analysed with regard to geogenic and anthropogenic influencing factors. Analysis includes review of 81 national and regional indoor radon surveys with varying sampling pattern, sample size and duration of measurements and detailed consideration of two regional surveys (Sverdlovsk oblast, Russia and Niška Banja, Serbia). The analysis of the geometric standard deviation revealed that main factors influencing the dispersion of indoor radon concentration over the territory are as follows: area of territory, sample size, characteristics of measurements technique, the radon geogenic potential, building construction characteristics and living habits. As shown for Sverdlovsk oblast and Niška Banja town the dispersion as quantified by GSD is reduced by restricting to certain levels of control factors. Application of the developed approach to characterization of the world population radon exposure is discussed. - Highlights: • Influence of lithosphere and anthroposphere on variance of indoor radon is found. • Level-by-level analysis reduces GSD by a factor of 1.9. • Worldwide GSD is underestimated.
Variance Component Selection With Applications to Microbiome Taxonomic Data
Directory of Open Access Journals (Sweden)
Jing Zhai
2018-03-01
Full Text Available High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.
Worldwide variance in the potential utilization of Gamma Knife radiosurgery.
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.
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.
Waste Isolation Pilot Plant no-migration variance petition
International Nuclear Information System (INIS)
1990-01-01
Section 3004 of RCRA allows EPA to grant a variance from the land disposal restrictions when a demonstration can be made that, to a reasonable degree of certainty, there will be no migration of hazardous constituents from the disposal unit for as long as the waste remains hazardous. Specific requirements for making this demonstration are found in 40 CFR 268.6, and EPA has published a draft guidance document to assist petitioners in preparing a variance request. Throughout the course of preparing this petition, technical staff from DOE, EPA, and their contractors have met frequently to discuss and attempt to resolve issues specific to radioactive mixed waste and the WIPP facility. The DOE believes it meets or exceeds all requirements set forth for making a successful ''no-migration'' demonstration. The petition presents information under five general headings: (1) waste information; (2) site characterization; (3) facility information; (4) assessment of environmental impacts, including the results of waste mobility modeling; and (5) analysis of uncertainties. Additional background and supporting documentation is contained in the 15 appendices to the petition, as well as in an extensive addendum published in October 1989
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...
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.
Variance decomposition-based sensitivity analysis via neural networks
International Nuclear Information System (INIS)
Marseguerra, Marzio; Masini, Riccardo; Zio, Enrico; Cojazzi, Giacomo
2003-01-01
This paper illustrates a method for efficiently performing multiparametric sensitivity analyses of the reliability model of a given system. These analyses are of great importance for the identification of critical components in highly hazardous plants, such as the nuclear or chemical ones, thus providing significant insights for their risk-based design and management. The technique used to quantify the importance of a component parameter with respect to the system model is based on a classical decomposition of the variance. When the model of the system is realistically complicated (e.g. by aging, stand-by, maintenance, etc.), its analytical evaluation soon becomes impractical and one is better off resorting to Monte Carlo simulation techniques which, however, could be computationally burdensome. Therefore, since the variance decomposition method requires a large number of system evaluations, each one to be performed by Monte Carlo, the need arises for possibly substituting the Monte Carlo simulation model with a fast, approximated, algorithm. Here we investigate an approach which makes use of neural networks appropriately trained on the results of a Monte Carlo system reliability/availability evaluation to quickly provide with reasonable approximation, the values of the quantities of interest for the sensitivity analyses. The work was a joint effort between the Department of Nuclear Engineering of the Polytechnic of Milan, Italy, and the Institute for Systems, Informatics and Safety, Nuclear Safety Unit of the Joint Research Centre in Ispra, Italy which sponsored the project
Concentration variance decay during magma mixing: a volcanic chronometer.
Perugini, Diego; De Campos, Cristina P; Petrelli, Maurizio; Dingwell, Donald B
2015-09-21
The mixing of magmas is a common phenomenon in explosive eruptions. Concentration variance is a useful metric of this process and its decay (CVD) with time is an inevitable consequence during the progress of magma mixing. In order to calibrate this petrological/volcanological clock we have performed a time-series of high temperature experiments of magma mixing. The results of these experiments demonstrate that compositional variance decays exponentially with time. With this calibration the CVD rate (CVD-R) becomes a new geochronometer for the time lapse from initiation of mixing to eruption. The resultant novel technique is fully independent of the typically unknown advective history of mixing - a notorious uncertainty which plagues the application of many diffusional analyses of magmatic history. Using the calibrated CVD-R technique we have obtained mingling-to-eruption times for three explosive volcanic eruptions from Campi Flegrei (Italy) in the range of tens of minutes. These in turn imply ascent velocities of 5-8 meters per second. We anticipate the routine application of the CVD-R geochronometer to the eruptive products of active volcanoes in future in order to constrain typical "mixing to eruption" time lapses such that monitoring activities can be targeted at relevant timescales and signals during volcanic unrest.
Mean-Variance-Validation Technique for Sequential Kriging Metamodels
International Nuclear Information System (INIS)
Lee, Tae Hee; Kim, Ho Sung
2010-01-01
The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean 0 validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean 0 validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels
PET image reconstruction: mean, variance, and optimal minimax criterion
International Nuclear Information System (INIS)
Liu, Huafeng; Guo, Min; Gao, Fei; Shi, Pengcheng; Xue, Liying; Nie, Jing
2015-01-01
Given the noise nature of positron emission tomography (PET) measurements, it is critical to know the image quality and reliability as well as expected radioactivity map (mean image) for both qualitative interpretation and quantitative analysis. While existing efforts have often been devoted to providing only the reconstructed mean image, we present a unified framework for joint estimation of the mean and corresponding variance of the radioactivity map based on an efficient optimal min–max criterion. The proposed framework formulates the PET image reconstruction problem to be a transformation from system uncertainties to estimation errors, where the minimax criterion is adopted to minimize the estimation errors with possibly maximized system uncertainties. The estimation errors, in the form of a covariance matrix, express the measurement uncertainties in a complete way. The framework is then optimized by ∞-norm optimization and solved with the corresponding H ∞ filter. Unlike conventional statistical reconstruction algorithms, that rely on the statistical modeling methods of the measurement data or noise, the proposed joint estimation stands from the point of view of signal energies and can handle from imperfect statistical assumptions to even no a priori statistical assumptions. The performance and accuracy of reconstructed mean and variance images are validated using Monte Carlo simulations. Experiments on phantom scans with a small animal PET scanner and real patient scans are also conducted for assessment of clinical potential. (paper)
... greatly advanced genetics research. The improved quality of genetic data has reduced the time required to identify a ... cases, a matter of months or even weeks. Genetic mapping data generated by the HGP's laboratories is freely accessible ...
Sankar, Pamela
2003-01-01
During the past 10 years, the number of genetic tests performed more than tripled, and public concern about genetic privacy emerged. The majority of states and the U.S. government have passed regulations protecting genetic information. However, research has shown that concerns about genetic privacy are disproportionate to known instances of information misuse. Beliefs in genetic determinacy explain some of the heightened concern about genetic privacy. Discussion of the debate over genetic testing within families illustrates the most recent response to genetic privacy concerns.
Spatially tuned normalization explains attention modulation variance within neurons.
Ni, Amy M; Maunsell, John H R
2017-09-01
Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism. NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical
Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction
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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
Estimating Additive and Dominance Variance for Liner Traits in ...
African Journals Online (AJOL)
merits ofpoteutialmarings from sire- maternal grandsire models with non- additive genetic effects..J. Dairy Sci. 72: 2592-2605. HOESCHELE, I., and VAN RADEN, P. M.. (199'): Rapid inversion ofdominance relationship matrices for non-inbred populations by including sire by dam subclass effects. J. Dairy Sci. 74:SS7-S69·.
Estimation of measurement variance in the context of environment statistics
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.
Risk Management - Variance Minimization or Lower Tail Outcome Elimination
DEFF Research Database (Denmark)
Aabo, Tom
2002-01-01
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......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......-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....
Draft no-migration variance petition. Volume 1
International Nuclear Information System (INIS)
1995-01-01
The Department of Energy is responsible for the disposition of transuranic (TRU) waste generated by national defense-related activities. Approximately 2,6 million cubic feet of these waste have been generated and are stored at various facilities across the country. The Waste Isolation Pilot Plant (WIPP), was sited and constructed to meet stringent disposal requirements. In order to permanently dispose of TRU waste, the DOE has elected to petition the US EPA for a variance from the Land Disposal Restrictions of RCRA. This document fulfills the reporting requirements for the petition. This report is Volume 1 which discusses the regulatory frame work, site characterization, facility description, waste description, environmental impact analysis, monitoring, quality assurance, long-term compliance analysis, and regulatory compliance assessment
Static models, recursive estimators and the zero-variance approach
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.
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...
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.
Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model
Deng, Guang-Feng; Lin, Woo-Tsong
This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.
Minimum variance linear unbiased estimators of loss and inventory
International Nuclear Information System (INIS)
Stewart, K.B.
1977-01-01
The article illustrates a number of approaches for estimating the material balance inventory and a constant loss amount from the accountability data from a sequence of accountability periods. The approaches all lead to linear estimates that have minimum variance. Techniques are shown whereby ordinary least squares, weighted least squares and generalized least squares computer programs can be used. Two approaches are recursive in nature and lend themselves to small specialized computer programs. Another approach is developed that is easy to program; could be used with a desk calculator and can be used in a recursive way from accountability period to accountability period. Some previous results are also reviewed that are very similar in approach to the present ones and vary only in the way net throughput measurements are statistically modeled. 5 refs
Cosmic variance in inflation with two light scalars
Energy Technology Data Exchange (ETDEWEB)
Bonga, Béatrice; Brahma, Suddhasattwa; Deutsch, Anne-Sylvie; Shandera, Sarah, E-mail: bpb165@psu.edu, E-mail: suddhasattwa.brahma@gmail.com, E-mail: asdeutsch@psu.edu, E-mail: shandera@gravity.psu.edu [Institute for Gravitation and the Cosmos and Physics Department, The Pennsylvania State University, University Park, PA, 16802 (United States)
2016-05-01
We examine the squeezed limit of the bispectrum when a light scalar with arbitrary non-derivative self-interactions is coupled to the inflaton. We find that when the hidden sector scalar is sufficiently light ( m ∼< 0.1 H ), the coupling between long and short wavelength modes from the series of higher order correlation functions (from arbitrary order contact diagrams) causes the statistics of the fluctuations to vary in sub-volumes. This means that observations of primordial non-Gaussianity cannot be used to uniquely reconstruct the potential of the hidden field. However, the local bispectrum induced by mode-coupling from these diagrams always has the same squeezed limit, so the field's locally determined mass is not affected by this cosmic variance.
Directory of Open Access Journals (Sweden)
G. R. Pasha
2006-07-01
Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.
Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling
Directory of Open Access Journals (Sweden)
Kang Miao Tan
2017-11-01
Full Text Available The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance. This is achieved by allowing electric vehicles charging (grid-to-vehicle whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid whenever the actual power grid loading is higher than the target loading. The vehicle-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA. The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various simulation investigations. This research proposal also recommends an appropriate setting for the power utility in terms of the selection of the target load based on the electric vehicle historical data.
Directory of Open Access Journals (Sweden)
Stevens Mark I
2007-08-01
Full Text Available Abstract Background The Central Limit Theorem (CLT is a statistical principle that states that as the number of repeated samples from any population increase, the variance among sample means will decrease and means will become more normally distributed. It has been conjectured that the CLT has the potential to provide benefits for group living in some animals via greater predictability in food acquisition, if the number of foraging bouts increases with group size. The potential existence of benefits for group living derived from a purely statistical principle is highly intriguing and it has implications for the origins of sociality. Results Here we show that in a social allodapine bee the relationship between cumulative food acquisition (measured as total brood weight and colony size accords with the CLT. We show that deviations from expected food income decrease with group size, and that brood weights become more normally distributed both over time and with increasing colony size, as predicted by the CLT. Larger colonies are better able to match egg production to expected food intake, and better able to avoid costs associated with producing more brood than can be reared while reducing the risk of under-exploiting the food resources that may be available. Conclusion These benefits to group living derive from a purely statistical principle, rather than from ecological, ergonomic or genetic factors, and could apply to a wide variety of species. This in turn suggests that the CLT may provide benefits at the early evolutionary stages of sociality and that evolution of group size could result from selection on variances in reproductive fitness. In addition, they may help explain why sociality has evolved in some groups and not others.
Stevens, Mark I; Hogendoorn, Katja; Schwarz, Michael P
2007-08-29
The Central Limit Theorem (CLT) is a statistical principle that states that as the number of repeated samples from any population increase, the variance among sample means will decrease and means will become more normally distributed. It has been conjectured that the CLT has the potential to provide benefits for group living in some animals via greater predictability in food acquisition, if the number of foraging bouts increases with group size. The potential existence of benefits for group living derived from a purely statistical principle is highly intriguing and it has implications for the origins of sociality. Here we show that in a social allodapine bee the relationship between cumulative food acquisition (measured as total brood weight) and colony size accords with the CLT. We show that deviations from expected food income decrease with group size, and that brood weights become more normally distributed both over time and with increasing colony size, as predicted by the CLT. Larger colonies are better able to match egg production to expected food intake, and better able to avoid costs associated with producing more brood than can be reared while reducing the risk of under-exploiting the food resources that may be available. These benefits to group living derive from a purely statistical principle, rather than from ecological, ergonomic or genetic factors, and could apply to a wide variety of species. This in turn suggests that the CLT may provide benefits at the early evolutionary stages of sociality and that evolution of group size could result from selection on variances in reproductive fitness. In addition, they may help explain why sociality has evolved in some groups and not others.
Genetic and environmental factors affecting birth size variation
DEFF Research Database (Denmark)
Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi
2018-01-01
Background: The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia......) and across birth cohorts, and how gestational age modifies these effects. Methods: Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling....... Results: The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased...
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Ma, Hui-qiang
2014-01-01
We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...
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...
Directory of Open Access Journals (Sweden)
Ellen Grippi Lira
Full Text Available ABSTRACT: Sunflower (Helianthus annuus L. is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD, days to start flowering (DFL based on flowering date in R5, chapter length (CL, weight of a thousand achenes (WTA, plant height (H and oil content (OilC of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.
The pricing of long and short run variance and correlation risk in stock returns
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
Spot Variance Path Estimation and its Application to High Frequency Jump Testing
Bos, C.S.; Janus, P.; Koopman, S.J.
2012-01-01
This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to
Variance bias analysis for the Gelbard's batch method
Energy Technology Data Exchange (ETDEWEB)
Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)
2014-05-15
In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.
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
Waste Isolation Pilot Plant No-Migration Variance Petition
International Nuclear Information System (INIS)
1990-03-01
The purpose of the WIPP No-Migration Variance Petition is to demonstrate, according to the requirements of RCRA section 3004(d) and 40 CFR section 268.6, that to a reasonable degree of certainty, there will be no migration of hazardous constituents from the facility for as long as the wastes remain hazardous. The DOE submitted the petition to the EPA in March 1989. Upon completion of its initial review, the EPA provided to DOE a Notice of Deficiencies (NOD). DOE responded to the EPA's NOD and met with the EPA's reviewers of the petition several times during 1989. In August 1989, EPA requested that DOE submit significant additional information addressing a variety of topics including: waste characterization, ground water hydrology, geology and dissolution features, monitoring programs, the gas generation test program, and other aspects of the project. This additional information was provided to EPA in January 1990 when DOE submitted Revision 1 of the Addendum to the petition. For clarity and ease of review, this document includes all of these submittals, and the information has been updated where appropriate. This document is divided into the following sections: Introduction, 1.0: Facility Description, 2.0: Waste Description, 3.0; Site Characterization, 4.0; Environmental Impact Analysis, 5.0; Prediction and Assessment of Infrequent Events, 6.0; and References, 7.0
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.
Beyond the GUM: variance-based sensitivity analysis in metrology
International Nuclear Information System (INIS)
Lira, I
2016-01-01
Variance-based sensitivity analysis is a well established tool for evaluating the contribution of the uncertainties in the inputs to the uncertainty in the output of a general mathematical model. While the literature on this subject is quite extensive, it has not found widespread use in metrological applications. In this article we present a succinct review of the fundamentals of sensitivity analysis, in a form that should be useful to most people familiarized with the Guide to the Expression of Uncertainty in Measurement (GUM). Through two examples, it is shown that in linear measurement models, no new knowledge is gained by using sensitivity analysis that is not already available after the terms in the so-called ‘law of propagation of uncertainties’ have been computed. However, if the model behaves non-linearly in the neighbourhood of the best estimates of the input quantities—and if these quantities are assumed to be statistically independent—sensitivity analysis is definitely advantageous for gaining insight into how they can be ranked according to their importance in establishing the uncertainty of the measurand. (paper)
Scale dependence in species turnover reflects variance in species occupancy.
McGlinn, Daniel J; Hurlbert, Allen H
2012-02-01
Patterns of species turnover may reflect the processes driving community dynamics across scales. While the majority of studies on species turnover have examined pairwise comparison metrics (e.g., the average Jaccard dissimilarity), it has been proposed that the species-area relationship (SAR) also offers insight into patterns of species turnover because these two patterns may be analytically linked. However, these previous links only apply in a special case where turnover is scale invariant, and we demonstrate across three different plant communities that over 90% of the pairwise turnover values are larger than expected based on scale-invariant predictions from the SAR. Furthermore, the degree of scale dependence in turnover was negatively related to the degree of variance in the occupancy frequency distribution (OFD). These findings suggest that species turnover diverges from scale invariance, and as such pairwise turnover and the slope of the SAR are not redundant. Furthermore, models developed to explain the OFD should be linked with those developed to explain species turnover to achieve a more unified understanding of community structure.
Improving computational efficiency of Monte Carlo simulations with variance reduction
International Nuclear Information System (INIS)
Turner, A.; Davis, A.
2013-01-01
CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)
Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC
International Nuclear Information System (INIS)
Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C
2007-01-01
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
A pattern recognition approach to transistor array parameter variance
da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.
2018-06-01
The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.
Simultaneous Monte Carlo zero-variance estimates of several correlated means
International Nuclear Information System (INIS)
Booth, T.E.
1998-01-01
Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown
Strategies for MCMC computation inquantitative genetics
DEFF Research Database (Denmark)
Waagepetersen, Rasmus; Ibánēz-Escriche, Noelia; Sorensen, Daniel
another extension of the linear mixed model introducing genetic random effects influencing the log residual variances of the observations thereby producing a genetically structured variance heterogeneity. Considerable computational problems arise when abandoning the standard linear mixed model. Maximum...... the various algorithms in the context of the heterogeneous variance model. Apart from being a model of great interest in its own right, this model has proven to be a hard test for MCMC methods. We compare the performances of the different algorithms when applied to three real datasets which differ markedly...... results of applying two MCMC schemes to data sets with pig litter sizes, rabbit litter sizes, and snail weights. Some concluding remarks are given in Section 5....
Genetic Characterization of Dog Personality Traits.
Ilska, Joanna; Haskell, Marie J; Blott, Sarah C; Sánchez-Molano, Enrique; Polgar, Zita; Lofgren, Sarah E; Clements, Dylan N; Wiener, Pamela
2017-06-01
The genetic architecture of behavioral traits in dogs is of great interest to owners, breeders, and professionals involved in animal welfare, as well as to scientists studying the genetics of animal (including human) behavior. The genetic component of dog behavior is supported by between-breed differences and some evidence of within-breed variation. However, it is a challenge to gather sufficiently large datasets to dissect the genetic basis of complex traits such as behavior, which are both time-consuming and logistically difficult to measure, and known to be influenced by nongenetic factors. In this study, we exploited the knowledge that owners have of their dogs to generate a large dataset of personality traits in Labrador Retrievers. While accounting for key environmental factors, we demonstrate that genetic variance can be detected for dog personality traits assessed using questionnaire data. We identified substantial genetic variance for several traits, including fetching tendency and fear of loud noises, while other traits revealed negligibly small heritabilities. Genetic correlations were also estimated between traits; however, due to fairly large SEs, only a handful of trait pairs yielded statistically significant estimates. Genomic analyses indicated that these traits are mainly polygenic, such that individual genomic regions have small effects, and suggested chromosomal associations for six of the traits. The polygenic nature of these traits is consistent with previous behavioral genetics studies in other species, for example in mouse, and confirms that large datasets are required to quantify the genetic variance and to identify the individual genes that influence behavioral traits. Copyright © 2017 by the Genetics Society of America.
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.
Is the experience of thermal pain genetics dependent?
DEFF Research Database (Denmark)
Horjales-Araujo, Emilia; Dahl, Joergen B
2015-01-01
It is suggested that genetic variations explain a significant portion of the variability in pain perception; therefore, increased understanding of pain-related genetic influences may identify new targets for therapies and treatments. The relative contribution of the different genes to the varianc...
Assessment of genetic diversity within sour cherry clones
DEFF Research Database (Denmark)
Clausen, Sabine Karin; Andersen, Sven Bode; Henriksen, K.
2013-01-01
of improved breeding material. However, no differences in allele profile were found between or within the clones, calling into question the extent of the available genetic diversity and indicating that the observed variance in yield may have to be explained by other genetic mechanisms, including epigenetic...
Genetic structure and diversity of the Neem Germplasm Bank from ...
African Journals Online (AJOL)
Particular
2013-05-15
May 15, 2013 ... ... fragment length polymorphism; AMOVA, molecular variance analysis. ... are technically simple, suitable for large-scale germplasm ... Brazil, our study aims to evaluate the genetic structure and genetic ... voltage of 100 V for 90 min. Gel was .... which does not justify an extra effort in labor (Bekessy et.
Analysis of genetic structure in Melia volkensii (Gurke.) populations ...
African Journals Online (AJOL)
Administrator
2Farm Forestry Programme, Kenya Forestry Research Institute, P. O. Box 20412, Nairobi, Kenya. Accepted 5 ... were used to estimate genetic distances between populations and for construction of neighbour-joining phenograms. Analysis of Molecular Variance (AMOVA) indicated significant genetic differentiation between ...
Genetic parameters for reproduction rate in the Tygerhoek Merino ...
African Journals Online (AJOL)
Dolling, 1963; Lewer, Rae & Wickham, 1983). Genetic. Number of lambing opportunities correlations involving EclEm and Ld/Lb, that showed. 2. 3. 4. 5 little genetic variation (Cloete &Heydenrych, 1987)were. Item particularly unstable. Negative between-sire variance. First set of data components prevented the estimation of ...
Quantitative genetic analysis of total glucosinolate, oil and protein ...
African Journals Online (AJOL)
Quantitative genetic analysis of total glucosinolate, oil and protein contents in Ethiopian mustard ( Brassica carinata A. Braun) ... Seeds were analyzed using HPLC (glucosinolates), NMR (oil) and NIRS (protein). Analyses of variance, Hayman's method of diallel analysis and a mixed linear model of genetic analysis were ...
Genetic variability of indigenous cowpea genotypes as determined ...
African Journals Online (AJOL)
Bayesian statistics coupled with the Markov chain Monte Carlo technique was applied to determine population structure, while the genetic variability was established by analysis of molecular variance. UPGMA analysis allowed the separation of the genotypes into three groups, but no relationship between the genetic and ...
AMOVA-based clustering of population genetic data
Meirmans, P.G.
2012-01-01
Determining the genetic structure of populations is becoming an increasingly important aspect of genetic studies. One of the most frequently used methods is the calculation of F-statistics using an Analysis of Molecular Variance (AMOVA). However, this has the drawback that the population hierarchy
Improving precision in gel electrophoresis by stepwisely decreasing variance components.
Schröder, Simone; Brandmüller, Asita; Deng, Xi; Ahmed, Aftab; Wätzig, Hermann
2009-10-15
Many methods have been developed in order to increase selectivity and sensitivity in proteome research. However, gel electrophoresis (GE) which is one of the major techniques in this area, is still known for its often unsatisfactory precision. Percental relative standard deviations (RSD%) up to 60% have been reported. In this case the improvement of precision and sensitivity is absolutely essential, particularly for the quality control of biopharmaceuticals. Our work reflects the remarkable and completely irregular changes of the background signal from gel to gel. This irregularity was identified as one of the governing error sources. These background changes can be strongly reduced by using a signal detection in the near-infrared (NIR) range. This particular detection method provides the most sensitive approach for conventional CCB (Colloidal Coomassie Blue) stained gels, which is reflected in a total error of just 5% (RSD%). In order to further investigate variance components in GE, an experimental Plackett-Burman screening design was performed. The influence of seven potential factors on the precision was investigated using 10 proteins with different properties analyzed by NIR detection. The results emphasized the individuality of the proteins. Completely different factors were identified to be significant for each protein. However, out of seven investigated parameters, just four showed a significant effect on some proteins, namely the parameters of: destaining time, staining temperature, changes of detergent additives (SDS and LDS) in the sample buffer, and the age of the gels. As a result, precision can only be improved individually for each protein or protein classes. Further understanding of the unique properties of proteins should enable us to improve the precision in gel electrophoresis.
Working Around Cosmic Variance: Remote Quadrupole Measurements of the CMB
Adil, Arsalan; Bunn, Emory
2018-01-01
Anisotropies in the CMB maps continue to revolutionize our understanding of the Cosmos. However, the statistical interpretation of these anisotropies is tainted with a posteriori statistics. The problem is particularly emphasized for lower order multipoles, i.e. in the cosmic variance regime of the power spectrum. Naturally, the solution lies in acquiring a new data set – a rather difficult task given the sample size of the Universe.The CMB temperature, in theory, depends on: the direction of photon propagation, the time at which the photons are observed, and the observer’s location in space. In existing CMB data, only the first parameter varies. However, as first pointed out by Kamionkowski and Loeb, a solution lies in making the so-called “Remote Quadrupole Measurements” by analyzing the secondary polarization produced by incoming CMB photons via the Sunyaev-Zel’dovich (SZ) effect. These observations allow us to measure the projected CMB quadrupole at the location and look-back time of a galaxy cluster.At low redshifts, the remote quadrupole is strongly correlated to the CMB anisotropy from our last scattering surface. We provide here a formalism for computing the covariance and relation matrices for both the two-point correlation function on the last scattering surface of a galaxy cluster and the cross correlation of the remote quadrupole with the local CMB. We then calculate these matrices based on a fiducial model and a non-standard model that suppresses power at large angles for ~104 clusters up to z=2. We anticipate to make a priori predictions of the differences between our expectations for the standard and non-standard models. Such an analysis is timely in the wake of the CMB S4 era which will provide us with an extensive SZ cluster catalogue.
Scaling of the mean and variance of population dynamics under fluctuating regimes.
Pertoldi, Cino; Faurby, S; Reed, D H; Knape, J; Björklund, M; Lundberg, P; Kaitala, V; Loeschcke, V; Bach, L A
2014-12-01
Theoretical ecologists have long sought to understand how the persistence of populations depends on the interactions between exogenous (biotic and abiotic) and endogenous (e.g., demographic and genetic) drivers of population dynamics. Recent work focuses on the autocorrelation structure of environmental perturbations and its effects on the persistence of populations. Accurate estimation of extinction times and especially determination of the mechanisms affecting extinction times is important for biodiversity conservation. Here we examine the interaction between environmental fluctuations and the scaling effect of the mean population size with its variance. We investigate how interactions between environmental and demographic stochasticity can affect the mean time to extinction, change optimal patch size dynamics, and how it can alter the often-assumed linear relationship between the census size and the effective population size. The importance of the correlation between environmental and demographic variation depends on the relative importance of the two types of variation. We found the correlation to be important when the two types of variation were approximately equal; however, the importance of the correlation diminishes as one source of variation dominates. The implications of these findings are discussed from a conservation and eco-evolutionary point of view.
Genetic modification and genetic determinism
Resnik, David B; Vorhaus, Daniel B
2006-01-01
In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions. PMID:16800884
A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.
Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio
2017-11-01
Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this
Theory and Practice in Quantitative Genetics
DEFF Research Database (Denmark)
Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C
2003-01-01
With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...
Behavior genetic modeling of human fertility
DEFF Research Database (Denmark)
Rodgers, J L; Kohler, H P; Kyvik, K O
2001-01-01
Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....
A comparison between temporal and subband minimum variance adaptive beamforming
Diamantis, Konstantinos; Voxen, Iben H.; Greenaway, Alan H.; Anderson, Tom; Jensen, Jørgen A.; Sboros, Vassilis
2014-03-01
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 with simulated synthetic aperture data obtained from Field II and is quantified by the Full-Width-Half-Maximum (FWHM), the Peak-Side-Lobe level (PSL) and the contrast level. From a point phantom, a full sequence of 128 emissions with one transducer element transmitting and all 128 elements receiving each time, provides a FWHM of 0.03 mm (0.14λ) for both implementations at a depth of 40 mm. This value is more than 20 times lower than the one achieved by conventional beamforming. The corresponding values of PSL are -58 dB and -63 dB for time and frequency domain MV beamformers, while a value no lower than -50 dB can be obtained from either Boxcar or Hanning weights. Interestingly, a single emission with central element #64 as the transmitting aperture provides results comparable to the full sequence. The values of FWHM are 0.04 mm and 0.03 mm and those of PSL are -42 dB and -46 dB for temporal and subband approaches. From a cyst phantom and for 128 emissions, the contrast level is calculated at -54 dB and -63 dB respectively at the same depth, with the initial shape of the cyst being preserved in contrast to conventional beamforming. The difference between the two adaptive beamformers is less significant in the case of a single emission, with the contrast level being estimated at -42 dB for the time domain and -43 dB for the frequency domain implementation. For the estimation of a single MV weight of a low resolution image formed by a single emission, 0.44 * 109 calculations per second are required for the temporal approach. The same numbers for the subband approach are 0.62 * 109 for the point and 1.33 * 109 for the cyst phantom. The comparison demonstrates similar
Directory of Open Access Journals (Sweden)
Siti Hidayati
2015-05-01
Full Text Available The aims of this study were (1 to analyze the phenotypic performance of Ettawa Grade (EG goat; (2to estimate the heritability of birth weight (BW, weaning weight (WW, yearling weight (YW, and geneticcorrelation between two body weights on the third different period; and (3 to analyze the variance andcovariance component of body weight. The material used were the exiting records of 437 EG goats in BalaiPembibitan Ternak Unggul dan Hijauan Pakan Ternak Pelaihari, South Kalimantan. These goats originatedfrom the crossing between 19 males and 216 females from periods of 2009 - 2012. Nested Design methodwas used to etimate the phenotypic correlation, heritability and genetic correlation. Variance componentswere determined from heritability estimation, while covariance components were determined from geneticcerrelation estimation. Phenotypic correlation between BW and WW, between BW and YW, and betweenWW and YW were 0.19 (low; 0.31 (medium; 0.65 (high; respectively. Heritability of BW, WW, and YW were0.43±0.23 (high; WW 0.27±0.19 (medium; and YW 1.01±0.38 (excludeof the h2 value, respectively.Genetic correlation between BW and WW, between BW and YW, and between WW and YW were -0.04(negative low; 0.49 (positive medium; and -0.41 (negative medium, respectively. Variance components ofbuck, ewes, and kid for BW were 10.76%; 37.16%; and 52.09%, respectively, for WW were 6.67%; 38.52%;and 54.81%, respectively, and for YW were 25.15%; 58.37%; and 16.43%, respectively. Covariancecomponents of buck, ewes, and kid between BW and WW were -3.91%; 66.45%; and 37.46%, respectively,between BW and YW were 65.68%; 16.50%; and 17.82, and between WW and YW were -5.14%; 83.87%; and21.28%, respectively. In conclusions variance component of ewes and kid were high in body weight at birthand weaning time. Therefore, selection should be conducted for body weight at birth and weaning time.
From Genetics to Genetic Algorithms
Indian Academy of Sciences (India)
Genetic algorithms (GAs) are computational optimisation schemes with an ... The algorithms solve optimisation problems ..... Genetic Algorithms in Search, Optimisation and Machine. Learning, Addison-Wesley Publishing Company, Inc. 1989.
From Genetics to Genetic Algorithms
Indian Academy of Sciences (India)
artificial genetic system) string feature or ... called the genotype whereas it is called a structure in artificial genetic ... assigned a fitness value based on the cost function. Better ..... way it has produced complex, intelligent living organisms capable of ...
Directory of Open Access Journals (Sweden)
Maklakov AA
2008-10-01
Full Text Available Abstract 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 selection. In particular, the evolution of adaptive female choice by indirect genetic benefits relies on the presence of genetic variation for fitness. Female choice by genetic benefits fall broadly into good genes (additive models and compatibility (non-additive models where the strength of selection is dictated by the genetic architecture of fitness. To characterize the genetic architecture of fitness, we employed a quantitative genetic design (the diallel cross in a population of the seed beetle Callosobruchus maculatus, which is known to exhibit post-copulatory female choice. From reciprocal crosses of inbred lines, we assayed egg production, egg-to-adult survival, and lifetime offspring production of the outbred F1 daughters (F1 productivity. Results We used the bio model to estimate six components of genetic and environmental variance in fitness. We found sizeable additive and non-additive genetic 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 be inclusive and should include quantifications of offspring reproductive success. We note that our estimate of additive genetic variance in F1 productivity (CVA = 14% is sufficient to generate indirect selection on female choice. However, our results also show that the major determinant of offspring fitness is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis
... clinical care in many areas of medicine. Assisted Reproductive Technology/Infertility Genetics Cancer Genetics Cardiovascular Genetics Cystic Fibrosis Genetics Fetal Intervention and Therapy Genetics Hematology Genetics Metabolic Genetics ...
Energy Technology Data Exchange (ETDEWEB)
Lanore, Jeanne-Marie [Commissariat a l' Energie Atomique - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Direction des Piles Atomiques, Departement des Etudes de Piles, Service d' Etudes de Protections de Piles (France)
1969-04-15
One of the main difficulties in Monte Carlo computations is the estimation of the results variance. Generally, only an apparent variance can be observed over a few calculations, often very different from the actual variance. By studying a large number of short calculations, the authors have tried to evaluate the real variance, and then to apply the obtained results to the optimization of the computations. The program used is the Poker one-dimensional Monte Carlo program. Calculations are performed in two types of fictitious environments: a body with constant cross section, without absorption, where all shocks are elastic and isotropic; a body with variable cross section (presenting a very pronounced peak and hole), with an anisotropy for high energy elastic shocks, and with the possibility of inelastic shocks (this body presents all the features that can appear in a real case)
Genetic influences on political ideologies
DEFF Research Database (Denmark)
Hatemi, Peter K; Medland, Sarah E; Klemmensen, Robert
2014-01-01
Almost 40 years ago, evidence from large studies of adult twins and their relatives suggested that between 30 and 60 % of the variance in social and political attitudes could be explained by genetic influences. However, these findings have not been widely accepted or incorporated into the dominant...... paradigms that explain the etiology of political ideology. This has been attributed in part to measurement and sample limitations, as well the relative absence of molecular genetic studies. Here we present results from original analyses of a combined sample of over 12,000 twins pairs, ascertained from nine...... different studies conducted in five democracies, sampled over the course of four decades. We provide evidence that genetic factors play a role in the formation of political ideology, regardless of how ideology is measured, the era, or the population sampled. The only exception is a question that explicitly...
Directory of Open Access Journals (Sweden)
Poivey Jean-Paul
2011-09-01
Full Text Available Abstract Background The pre-weaning growth rate of lambs, an important component of meat market production, is affected by maternal and direct genetic effects. The French genetic evaluation model takes into account the number of lambs suckled by applying a multiplicative factor (1 for a lamb reared as a single, 0.7 for twin-reared lambs to the maternal genetic effect, in addition to including the birth*rearing type combination as a fixed effect, which acts on the mean. However, little evidence has been provided to justify the use of this multiplicative model. The two main objectives of the present study were to determine, by comparing models of analysis, 1 whether pre-weaning growth is the same trait in single- and twin-reared lambs and 2 whether the multiplicative coefficient represents a good approach for taking this possible difference into account. Methods Data on the pre-weaning growth rate, defined as the average daily gain from birth to 45 days of age on 29,612 Romane lambs born between 1987 and 2009 at the experimental farm of La Sapinière (INRA-France were used to compare eight models that account for the number of lambs per dam reared in various ways. Models were compared using the Akaike information criteria. Results The model that best fitted the data assumed that 1 direct (maternal effects correspond to the same trait regardless of the number of lambs reared, 2 the permanent environmental effects and variances associated with the dam depend on the number of lambs reared and 3 the residual variance depends on the number of lambs reared. Even though this model fitted the data better than a model that included a multiplicative coefficient, little difference was found between EBV from the different models (the correlation between EBV varied from 0.979 to 0.999. Conclusions Based on experimental data, the current genetic evaluation model can be improved to better take into account the number of lambs reared. Thus, it would be of
A Mean-Variance Criterion for Economic Model Predictive Control of Stochastic Linear Systems
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik
2014-01-01
, the tractability of the resulting optimal control problem is addressed. We use a power management case study to compare different variations of the mean-variance strategy with EMPC based on the certainty equivalence principle. The certainty equivalence strategy is much more computationally efficient than the mean......-variance strategies, but it does not account for the variance of the uncertain parameters. Openloop simulations suggest that a single-stage mean-variance approach yields a significantly lower operating cost than the certainty equivalence strategy. In closed-loop, the single-stage formulation is overly conservative...... be modified to perform almost as well as the two-stage mean-variance formulation. Nevertheless, we argue that the mean-variance approach can be used both as a strategy for evaluating less computational demanding methods such as the certainty equivalence method, and as an individual control strategy when...
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Directory of Open Access Journals (Sweden)
Hui-qiang Ma
2014-01-01
Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.
Direct and maternal genetic effects for birth weight in dorper and ...
African Journals Online (AJOL)
Variance components for birth (BWT) in Dorper and Mutton Merino sheep were estimated by Average Information Restricted Maximum Likelihood (AIREML). Animal model was fitted allowing for genetic maternal effects and a genetic covariance between direct and maternal effects. Estimates of heritability for direct genetic ...
Genetic parameters in a Swine Population
Directory of Open Access Journals (Sweden)
Dana Popa
2010-05-01
Full Text Available The estimation of the variance-covariance components is a very important step in animal breeding because these components are necessary for: estimation of the genetic parameters, prediction of the breeding value and design of animal breeding programs. The estimation of genetic parameters is the first step in the development of a swine breeding program, using artificial insemination. Various procedures exist for estimation of heritability. There are three major procedures used for estimating heritability: analysis of variance (ANOVA, parents-offspring regression and restricted maximum likelihood (REML. By using ANOVA methodology or regression method it is possible to obtain aberrant values of genetic parameters (negative or over unit value of heritability coefficient, for example which can not be interpreting because is out of biological limits.
Bright, Molly G.; Murphy, Kevin
2015-01-01
Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed ...
Kerstens, Kristiaan; Mounier, Amine; Van de Woestyne, Ignace
2008-01-01
The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio fro...
Institute of Scientific and Technical Information of China (English)
Li Shu; Zhuo Jiashou; Ren Qingwen
2000-01-01
In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.
A characterization of optimal portfolios under the tail mean-variance criterion
Owadally, I.; Landsman, Z.
2013-01-01
The tail mean–variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean–variance framework. The tail mean–variance criterion...
A geometric approach to multiperiod mean variance optimization of assets and liabilities
Leippold, Markus; Trojani, Fabio; Vanini, Paolo
2005-01-01
We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the corresponding multi period mean variance frontiers are spanned by an orthogonal basis of dynamic returns. Spec...
Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V
2009-12-01
Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.
Estimating integrated variance in the presence of microstructure noise using linear regression
Holý, Vladimír
2017-07-01
Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.
Variance-in-Mean Effects of the Long Forward-Rate Slope
DEFF Research Database (Denmark)
Christiansen, Charlotte
2005-01-01
This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....
Benedetti-Cecchi, Lisandro; Bertocci, Iacopo; Vaselli, Stefano; Maggi, Elena
2006-10-01
Extreme climate events produce simultaneous changes to the mean and to the variance of climatic variables over ecological time scales. While several studies have investigated how ecological systems respond to changes in mean values of climate variables, the combined effects of mean and variance are poorly understood. We examined the response of low-shore assemblages of algae and invertebrates of rocky seashores in the northwest Mediterranean to factorial manipulations of mean intensity and temporal variance of aerial exposure, a type of disturbance whose intensity and temporal patterning of occurrence are predicted to change with changing climate conditions. Effects of variance were often in the opposite direction of those elicited by changes in the mean. Increasing aerial exposure at regular intervals had negative effects both on diversity of assemblages and on percent cover of filamentous and coarsely branched algae, but greater temporal variance drastically reduced these effects. The opposite was observed for the abundance of barnacles and encrusting coralline algae, where high temporal variance of aerial exposure either reversed a positive effect of mean intensity (barnacles) or caused a negative effect that did not occur under low temporal variance (encrusting algae). These results provide the first experimental evidence that changes in mean intensity and temporal variance of climatic variables affect natural assemblages of species interactively, suggesting that high temporal variance may mitigate the ecological impacts of ongoing and predicted climate changes.
The genotype-environment interaction variance in rice-seed protein determination
International Nuclear Information System (INIS)
Ismachin, M.
1976-01-01
Many environmental factors influence the protein content of cereal seed. This fact procured difficulties in breeding for protein. Yield is another example on which so many environmental factors are of influence. The length of time required by the plant to reach maturity, is also affected by the environmental factors; even though its effect is not too decisive. In this investigation the genotypic variance and the genotype-environment interaction variance which contribute to the total variance or phenotypic variance was analysed, with purpose to give an idea to the breeder how selection should be made. It was found that genotype-environment interaction variance is larger than the genotypic variance in contribution to total variance of protein-seed determination or yield. In the analysis of the time required to reach maturity it was found that genotypic variance is larger than the genotype-environment interaction variance. It is therefore clear, why selection for time required to reach maturity is much easier than selection for protein or yield. Selected protein in one location may be different from that to other locations. (author)
Optimal control of LQG problem with an explicit trade-off between mean and variance
Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang
2011-12-01
For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.
Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response
Directory of Open Access Journals (Sweden)
Muqaddas Javed
2014-09-01
Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.
A mean–variance objective for robust production optimization in uncertain geological scenarios
DEFF Research Database (Denmark)
Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne
2014-01-01
directly. In the mean–variance bi-criterion objective function risk appears directly, it also considers an ensemble of reservoir models, and has robust optimization as a special extreme case. The mean–variance objective is common for portfolio optimization problems in finance. The Markowitz portfolio...... optimization problem is the original and simplest example of a mean–variance criterion for mitigating risk. Risk is mitigated in oil production by including both the expected NPV (mean of NPV) and the risk (variance of NPV) for the ensemble of possible reservoir models. With the inclusion of the risk...
The Variance between Recommended and Nursing Staff Levels at Womack Army Medical Center
National Research Council Canada - National Science Library
Holcek, Robert A
2007-01-01
.... This study considered five possible rationales for the existing variances - workload changes, staff experience, observation patients, recovery patients, and outpatient procedures - for 117 work...
Genetic divergence of tomato subsamples
Directory of Open Access Journals (Sweden)
André Pugnal Mattedi
2014-02-01
Full Text Available Understanding the genetic variability of a species is crucial for the progress of a genetic breeding program and requires characterization and evaluation of germplasm. This study aimed to characterize and evaluate 101 tomato subsamples of the Salad group (fresh market and two commercial controls, one of the Salad group (cv. Fanny and another of the Santa Cruz group (cv. Santa Clara. Four experiments were conducted in a randomized block design with three replications and five plants per plot. The joint analysis of variance was performed and characteristics with significant complex interaction between control and experiment were excluded. Subsequently, the multicollinearity diagnostic test was carried out and characteristics that contributed to severe multicollinearity were excluded. The relative importance of each characteristics for genetic divergence was calculated by the Singh's method (Singh, 1981, and the less important ones were excluded according to Garcia (1998. Results showed large genetic divergence among the subsamples for morphological, agronomic and organoleptic characteristics, indicating potential for genetic improvement. The characteristics total soluble solids, mean number of good fruits per plant, endocarp thickness, mean mass of marketable fruit per plant, total acidity, mean number of unmarketable fruit per plant, internode diameter, internode length, main stem thickness and leaf width contributed little to the genetic divergence between the subsamples and may be excluded in future studies.
Education modifies genetic and environmental influences on BMI
DEFF Research Database (Denmark)
Johnson, Wendy; Kyvik, Kirsten Ohm; Skytthe, Axel
2011-01-01
environmental correlations between education and BMI differed by level of education, analyzing women and men separately. Correlations between education and BMI were -.13 in women, -.15 in men. High BMI's were less frequent among well-educated participants, generating less variance. In women, this was due...... to restriction of all forms of variance, overall by a factor of about 2. In men, genetic variance did not vary with education, but results for shared and nonshared environmental variance were similar to those for women. The contributions of the shared environment to the correlations between education and BMI......Obesity is more common among the less educated, suggesting education-related environmental triggers. Such triggers may act differently dependent on genetic and environmental predisposition to obesity. In a Danish Twin Registry survey, 21,522 twins of same-sex pairs provided zygosity, height, weight...
Genetics and intelligence differences: five special findings
Plomin, R; Deary, I J
2015-01-01
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic
Directory of Open Access Journals (Sweden)
Haley Christopher S
2009-01-01
Full Text Available Abstract Introduction Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis. Results Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse. Conclusion Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.
Genetic variability and heritability estimates of some polygenic traits in upland cotton
International Nuclear Information System (INIS)
Baloch, M.J.
2004-01-01
Plant breeders are more interested in genetic variance rather than phenotypic variance because it is amenable to selection and bring further improvement in the character. Twenty-eight F/sub 2/ progenies were tested in two environments so as to predict genetic variances, heritability estimates and genetic gains. Mean squares for locations were significant for all the five traits suggesting that genotypes performed differently under varying environments. Genetic variances, in most cases, however, were about equal to that of phenotypic variances consequently giving high heritability estimates and significant genetic gains. The broad sense heritability estimates were; 94.2, 92.9, 33.6, 81.9 and 86.9% and genetic gains were; 30.19, 10.55,0.20,0.89 and 1.76 in seed cotton yield, bolls per plant, lint %, fibre length and fibre uniformity ratio, respectively. Substantial genetic variances and high heritability estimates implied that these characters could be improved through selection from segregating populations. (author)
Genetic component in learning ability in bees.
Kerr, W E; Moura Duarte, F A; Oliveira, R S
1975-10-01
Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.
Variance to mean ratio, R(t), for poisson processes on phylogenetic trees.
Goldman, N
1994-09-01
The ratio of expected variance to mean, R(t), of numbers of DNA base substitutions for contemporary sequences related by a "star" phylogeny is widely seen as a measure of the adherence of the sequences' evolution to a Poisson process with a molecular clock, as predicted by the "neutral theory" of molecular evolution under certain conditions. A number of estimators of R(t) have been proposed, all predicted to have mean 1 and distributions based on the chi 2. Various genes have previously been analyzed and found to have values of R(t) far in excess of 1, calling into question important aspects of the neutral theory. In this paper, I use Monte Carlo simulation to show that the previously suggested means and distributions of estimators of R(t) are highly inaccurate. The analysis is applied to star phylogenies and to general phylogenetic trees, and well-known gene sequences are reanalyzed. For star phylogenies the results show that Kimura's estimators ("The Neutral Theory of Molecular Evolution," Cambridge Univ. Press, Cambridge, 1983) are unsatisfactory for statistical testing of R(t), but confirm the accuracy of Bulmer's correction factor (Genetics 123: 615-619, 1989). For all three nonstar phylogenies studied, attained values of all three estimators of R(t), although larger than 1, are within their true confidence limits under simple Poisson process models. This shows that lineage effects can be responsible for high estimates of R(t), restoring some limited confidence in the molecular clock and showing that the distinction between lineage and molecular clock effects is vital.(ABSTRACT TRUNCATED AT 250 WORDS)
Directory of Open Access Journals (Sweden)
Pascal Schopp
2017-11-01
Full Text Available A major application of genomic prediction (GP in plant breeding is the identification of superior inbred lines within families derived from biparental crosses. When models for various traits were trained within related or unrelated biparental families (BPFs, experimental studies found substantial variation in prediction accuracy (PA, but little is known about the underlying factors. We used SNP marker genotypes of inbred lines from either elite germplasm or landraces of maize (Zea mays L. as parents to generate in silico 300 BPFs of doubled-haploid lines. We analyzed PA within each BPF for 50 simulated polygenic traits, using genomic best linear unbiased prediction (GBLUP models trained with individuals from either full-sib (FSF, half-sib (HSF, or unrelated families (URF for various sizes (Ntrain of the training set and different heritabilities (h2 . In addition, we modified two deterministic equations for forecasting PA to account for inbreeding and genetic variance unexplained by the training set. Averaged across traits, PA was high within FSF (0.41–0.97 with large variation only for Ntrain < 50 and h2 < 0.6. For HSF and URF, PA was on average ∼40–60% lower and varied substantially among different combinations of BPFs used for model training and prediction as well as different traits. As exemplified by HSF results, PA of across-family GP can be very low if causal variants not segregating in the training set account for a sizeable proportion of the genetic variance among predicted individuals. Deterministic equations accurately forecast the PA expected over many traits, yet cannot capture trait-specific deviations. We conclude that model training within BPFs generally yields stable PA, whereas a high level of uncertainty is encountered in across-family GP. Our study shows the extent of variation in PA that must be at least reckoned with in practice and offers a starting point for the design of training sets composed of multiple BPFs.
Genetic modification and genetic determinism
Directory of Open Access Journals (Sweden)
Vorhaus Daniel B
2006-06-01
Full Text Available Abstract In this article we examine four objections to the genetic modification of human beings: the freedom argument, the giftedness argument, the authenticity argument, and the uniqueness argument. We then demonstrate that each of these arguments against genetic modification assumes a strong version of genetic determinism. Since these strong deterministic assumptions are false, the arguments against genetic modification, which assume and depend upon these assumptions, are therefore unsound. Serious discussion of the morality of genetic modification, and the development of sound science policy, should be driven by arguments that address the actual consequences of genetic modification for individuals and society, not by ones propped up by false or misleading biological assumptions.
On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models
Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.
2017-12-01
Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.
Bright, Molly G; Murphy, Kevin
2015-07-01
Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.
Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov
2016-01-01
Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002
On Mean-Variance Hedging of Bond Options with Stochastic Risk Premium Factor
Aihara, ShinIchi; Bagchi, Arunabha; Kumar, Suresh K.
2014-01-01
We consider the mean-variance hedging problem for pricing bond options using the yield curve as the observation. The model considered contains infinite-dimensional noise sources with the stochastically- varying risk premium. Hence our model is incomplete. We consider mean-variance hedging under the
Investor preferences for oil spot and futures based on mean-variance and stochastic dominance
H.H. Lean (Hooi Hooi); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)
2010-01-01
textabstractThis paper examines investor preferences for oil spot and futures based on mean-variance (MV) and stochastic dominance (SD). The mean-variance criterion cannot distinct the preferences of spot and market whereas SD tests leads to the conclusion that spot dominates futures in the downside
Within-category variance and lexical tone discrimination in native and non-native speakers
Hoffmann, C.W.G.; Sadakata, M.; Chen, A.; Desain, P.W.M.; McQueen, J.M.; Gussenhove, C.; Chen, Y.; Dediu, D.
2014-01-01
In this paper, we show how acoustic variance within lexical tones in disyllabic Mandarin Chinese pseudowords affects discrimination abilities in both native and non-native speakers of Mandarin Chinese. Within-category acoustic variance did not hinder native speakers in discriminating between lexical
Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov
2015-10-01
Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.
29 CFR 1926.2 - Variances from safety and health standards.
2010-07-01
... from safety and health standards. (a) Variances from standards which are, or may be, published in this... 29 Labor 8 2010-07-01 2010-07-01 false Variances from safety and health standards. 1926.2 Section 1926.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...
Using variances to comply with resource conservation and recovery act treatment standards
International Nuclear Information System (INIS)
Ranek, N.L.
2002-01-01
When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.
International Nuclear Information System (INIS)
Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars
2012-01-01
Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.
Bayesian evaluation of constrained hypotheses on variances of multiple independent groups
Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.
2017-01-01
Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations
Impact of time-inhomogeneous jumps and leverage type effects on returns and realised variances
DEFF Research Database (Denmark)
Veraart, Almut
This paper studies the effect of time-inhomogeneous jumps and leverage type effects on realised variance calculations when the logarithmic asset price is given by a Lévy-driven stochastic volatility model. In such a model, the realised variance is an inconsistent estimator of the integrated...
Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.
Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J
2015-01-01
Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.
Accounting for non-stationary variance in geostatistical mapping of soil properties
Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.
2018-01-01
Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)
Fan, Weihua; Hancock, Gregory R.
2012-01-01
This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…
An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests
Attali, Yigal
2010-01-01
Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…
On the multiplicity of option prices under CEV with positive elasticity of variance
Veestraeten, D.
2017-01-01
The discounted stock price under the Constant Elasticity of Variance model is not a martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the price for which put-call parity holds and the price that represents the lowest cost of
On the multiplicity of option prices under CEV with positive elasticity of variance
Veestraeten, D.
2014-01-01
The discounted stock price under the Constant Elasticity of Variance (CEV) model is a strict local martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the risk-neutral call price and an alternative price that is linked to the unique
Some novel inequalities for fuzzy variables on the variance and its rational upper bound
Directory of Open Access Journals (Sweden)
Xiajie Yi
2016-02-01
Full Text Available Abstract Variance is of great significance in measuring the degree of deviation, which has gained extensive usage in many fields in practical scenarios. The definition of the variance on the basis of the credibility measure was first put forward in 2002. Following this idea, the calculation of the accurate value of the variance for some special fuzzy variables, like the symmetric and asymmetric triangular fuzzy numbers and the Gaussian fuzzy numbers, is presented in this paper, which turns out to be far more complicated. Thus, in order to better implement variance in real-life projects like risk control and quality management, we suggest a rational upper bound of the variance based on an inequality, together with its calculation formula, which can largely simplify the calculation process within a reasonable range. Meanwhile, some discussions between the variance and its rational upper bound are presented to show the rationality of the latter. Furthermore, two inequalities regarding the rational upper bound of variance and standard deviation of the sum of two fuzzy variables and their individual variances and standard deviations are proved. Subsequently, some numerical examples are illustrated to show the effectiveness and the feasibility of the proposed inequalities.
Understanding the Degrees of Freedom of Sample Variance by Using Microsoft Excel
Ding, Jian-Hua; Jin, Xian-Wen; Shuai, Ling-Ying
2017-01-01
In this article, the degrees of freedom of the sample variance are simulated by using the Visual Basic for Applications of Microsoft Excel 2010. The simulation file dynamically displays why the sample variance should be calculated by dividing the sum of squared deviations by n-1 rather than n, which is helpful for students to grasp the meaning of…
Analysis of force variance for a continuous miner drum using the Design of Experiments method
Energy Technology Data Exchange (ETDEWEB)
S. Somanchi; V.J. Kecojevic; C.J. Bise [Pennsylvania State University, University Park, PA (United States)
2006-06-15
Continuous miners (CMs) are excavating machines designed to extract a variety of minerals by underground mining. The variance in force experienced by the cutting drum is a very important aspect that must be considered during drum design. A uniform variance essentially means that an equal load is applied on the individual cutting bits and this, in turn, enables better cutting action, greater efficiency, and longer bit and machine life. There are certain input parameters used in the drum design whose exact relationships with force variance are not clearly understood. This paper determines (1) the factors that have a significant effect on the force variance of the drum and (2) the values that can be assigned to these factors to minimize the force variance. A computer program, Continuous Miner Drum (CMD), was developed in collaboration with Kennametal, Inc. to facilitate the mechanical design of CM drums. CMD also facilitated data collection for determining significant factors affecting force variance. Six input parameters, including centre pitch, outer pitch, balance angle, shift angle, set angle and relative angle were tested at two levels. Trials were configured using the Design of Experiments (DoE) method where 2{sup 6} full-factorial experimental design was selected to investigate the effect of these factors on force variance. Results from the analysis show that all parameters except balance angle, as well as their interactions, significantly affect the force variance.
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Terasvirta, Timo
The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH...... models. An application to exchange rate returns is included....
Genetic parameters of growth, body, and egg traits in Japanese quails
African Journals Online (AJOL)
SARAH
2014-07-31
Jul 31, 2014 ... egg traits as well as genetic and phenotypic relationships between these traits in Japanese quails reared in the ... Japanese quail is the smallest avian species farmed .... 2 = cross classified “family” variance component.
Phillips, John
1973-01-01
Presents a review of genetic engineering, in which the genotypes of plants and animals (including human genotypes) may be manipulated for the benefit of the human species. Discusses associated problems and solutions and provides an extensive bibliography of literature relating to genetic engineering. (JR)
DEFF Research Database (Denmark)
Tupasela, Aaro
2016-01-01
inheritance as a way to unify populations within politically and geographically bounded areas. Thus, new genetics have contributed to the development of genetic romanticisms, whereby populations (human, plant, and animal) can be delineated and mobilized through scientific and medical practices to represent...
Teacher quality moderates the genetic effects on early reading.
Taylor, J; Roehrig, A D; Soden Hensler, B; Connor, C M; Schatschneider, C
2010-04-23
Children's reading achievement is influenced by genetics as well as by family and school environments. The importance of teacher quality as a specific school environmental influence on reading achievement is unknown. We studied first- and second-grade students in Florida from schools representing diverse environments. Comparison of monozygotic and dizygotic twins, differentiating genetic similarities of 100% and 50%, provided an estimate of genetic variance in reading achievement. Teacher quality was measured by how much reading gain the non-twin classmates achieved. The magnitude of genetic variance associated with twins' oral reading fluency increased as the quality of their teacher increased. In circumstances where the teachers are all excellent, the variability in student reading achievement may appear to be largely due to genetics. However, poor teaching impedes the ability of children to reach their potential.
How the Weak Variance of Momentum Can Turn Out to be Negative
Feyereisen, M. R.
2015-05-01
Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.
International Nuclear Information System (INIS)
Campanelli, Mark; Kacker, Raghu; Kessel, Rüdiger
2013-01-01
A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)
Simultaneous Monte Carlo zero-variance estimates of several correlated means
International Nuclear Information System (INIS)
Booth, T.E.
1997-08-01
Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems
Genetic Parameters of Common Wheat in Nepal
Directory of Open Access Journals (Sweden)
Bal Krishna Joshi
2015-12-01
Full Text Available Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correlated response. Differences between phenotypic and genotypic variances in heading days, maturity days and plant height were not large. Grain yield and plant height showed the highest phenotypic (18.189% and genotypic (12.06% coefficient of variances, respectively. Phenotypic covariance was higher than genotypic and environmental covariance in most of the traits. The highest heritability and realized heritability were of heading days followed by maturity days. Genetic gain for plant height was the highest. Co-heritability of 1000-grain weight with tillers number was the highest. The highest correlated response was expressed by grain yield with tillers number. This study indicates the possibility of improving wheat genotypes through selection utilizing existing variation in these traits.