搜索结果: 1-15 共查到“empirical Bayes”相关记录20条 . 查询时间(0.484 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...
NEEDLES AND STRAW IN HAYSTACKS: EMPIRICAL BAYES ESTIMATES OF POSSIBLY SPARSE SEQUENCES
HAYSTACKS NEEDLES AND STRAW
2015/8/20
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...
Two modeling strategies for empirical Bayes estimation
f-modeling g-modeling Bayes rule in terms of f
2015/8/20
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 ...
Empirical Bayes Estimates for Large-Scale Prediction Problems
microarray prediction empirical Bayes shrunken centroids
2015/8/20
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....
Microarrays, Empirical Bayes, and the Two-Groups Model
Empirical Bayes the Two-Groups Model
2015/8/20
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...
Detecting mutations in mixed sample sequencing data using empirical Bayes
Detecting mutations mixed sample sequencing data empirical Bayes
2012/11/23
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...
A nonparametric empirical Bayes framework for large-scale multiple testing
Dirichlet process marginal likelihood mixture model
2011/7/6
We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-n...
Empirical Bayes inference for the Burr model based on records
Burr type XII model record values
2010/9/25
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.
Large-scale interval and point estimates from an empirical Bayes extension of confidence posteriors
Large-scale interval point estimates empirical Bayes extension confidence posteriors
2011/3/4
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...
Large-scale interval and point estimates from an empirical Bayes extension of confidence posteriors
Large-scale interval point estimates empirical Bayes extension
2011/1/6
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...
Large-scale interval and point estimates from an empirical Bayes extension of confidence posteriors
Large-scale interval point estimates empirical Bayes
2011/1/4
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...
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
Bayes and empirical-Bayes multiplicity adjustment variable-selection problem
2010/11/15
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...
An empirical Bayes mixture method for effect size and false discovery rate estimation
Empirical Bayes false discovery rate effect size estimation
2010/10/19
Many statistical problems involve data from thousands of parallel cases. Each case has some associated effect size, and most cases will have no effect. It is often important to estimate the effect siz...
Decision Approach and Empirical Bayes FCR-Controlling Interval for Mixed Prior Model
Decision Bayes Loss Function Simultaneous Intervals
2010/3/17
In this paper, I apply the decision theory and empirical Bayesian
approach to construct confidence intervals for selected populations when
true parameters follow a mixture prior distribution. A loss...