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搜索结果: 1-11 共查到数学 Empirical Bayes相关记录11条 . 查询时间(0.108 秒)
This paper explores a class of empirical Bayes methods for levedependent threshold selection in wavelet shrinkage. The prior considered for each wavelet coefficient is a mixture of an atom of p...
An empirical Bayes approach to the estimation of possibly sparse sequences observed in Gaussian white noise is set out and investigated. The prior considered is a mixture of an atom of probability a...
Empirical Bayes methods use the data from parallel experiments, for instance observtions Xk  N (k;1) for k = 1;2; : : : ; N, to estimate the conditional distributions kjXk. There are two main estima...
This article is intended as an expositional overview of empirical Bayes modeling methodology, presented in a simpli ed framework that reduces technical diculties. The two principal empirical Bayes ...
Classical prediction methods such as Fisher's linear discriminant function were designed for small-scale problems, where the number of predictors N is much smaller than the number of observations n....
The classic frequentist theory of hypothesis testing developed by Neyman, Pearson, and Fisher has a claim to being the Twentieth Century’s most influential piece of applied mathematics. Somethi...
We develop statistically based methods to detect single nucleotide DNA mutations in next generation sequencing data. Sequencing generates counts of the number of times each base was observed at hundre...
In this paper, the empirical Bayes estimators are derived for the reliability index of Burr type XII model. The Monte-Carlo method are used to investigate the accuracy of the estimators.
In statistical genomics, bioinformatics, and neuroinformatics, truth values of multiple hypotheses are often modeled as random quantities of a common mixture distribution in order to estimate false d...
The proposed approach extends the confidence posterior distribution to the semi-parametric empirical Bayes setting. Whereas the Bayesian posterior is defined in terms of a prior distribution condition...
This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens a...

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