نتایج جستجو برای: bayes b
تعداد نتایج: 916874 فیلتر نتایج به سال:
Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic se...
The current study was carried out to evaluate accuracy of some Bayesian methods for genomic breeding values prediction for threshold traits with different types of genetic architecture based on distribution of gene effect and QTL numbers. A genome consisted of 3 chromosomes of 100 CM with 2000 single nucleotide polymorphisms (SNP) was simulated. The QTL numbers were 0.01, 0.05 and 0.1 of total ...
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-lineari...
In the class of normal regression models with a finite number of regressors, and for a wide class of prior distributions, a Bayesian model selection procedure based on the Bayes factor is consistent [Casella and Moreno J. Amer. Statist. Assoc. 104 (2009) 1261–1271]. However, in models where the number of parameters increases as the sample size increases, properties of the Bayes factor are not t...
Gaussian processes are a class of flexible nonparametric Bayesian tools that widely used across the sciences, and in industry, to model complex data sources. Key applying process models is availability well-developed open source software, which available many programming languages. In this paper, we present tutorial GaussianProcesses.jl package has been developed for Julia language. utilizes in...
Based on a given Bayesian model of multivariate normal with known variance matrix we will find an empirical Bayes confidence interval for the mean vector components which have normal distribution. We will find this empirical Bayes confidence interval as a conditional form on ancillary statistic. In both cases (i.e. conditional and unconditional empirical Bayes confidence interval), the empiri...
background breast cancer (bc) is the most common cancer in iranian women. studying the mortality statistics is important to monitor the effects of screening programs or the influence of earlier diagnosis on the burden of this chronic disease. misclassification is still a problem in the iranian death registry data and about 20% of death statistics are recorded in misclassified categories. object...
ERRATA delete optimal Section accommodate R(t,k) vi ci nity change b-a to a-b Bayes risk It easily follows (by induction) from (9) and (21) ...
Within the Kolmogorov theory of probability, Bayes’ rule allows one to perform statistical inference by relating conditional probabilities to unconditional probabilities. As we show here, however, there is a continuous set of alternative inference rules that yield the same results, and that may have computational or practical advantages for certain problems. We formulate generalized axioms for ...
There have been considerable methodological developments of Bayes factors for hypothesis testing in the social and behavioral sciences, related fields. This development is due to flexibility factor multiple hypotheses simultaneously, ability test complex involving equality as well order constraints on parameters interest, interpretability outcome weight evidence provided by data support competi...
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