statistical inference via empirical bayes approach for stationary and dynamic contingency tables
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An empirical Bayes approach to inferring large-scale gene association networks
MOTIVATION: Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis where the sample size is small compared to the number of considered genes. Th
Optimal post-selection inference for sparse signals: a nonparametric empirical Bayes approach
Summary Many recently developed Bayesian methods focus on sparse signal detection. However, much less work has been done on the natural follow-up question: how does one make valid inferences for the magnitude of those signals after selection? Ordinary Bayesian credible intervals
The Empirical Bayes Approach to Statistical Decision Problems
The empirical Bayes approach to statistical decision problems is applicable when the same decision problem presents itself repeatedly and independently with a fixed but unknown a priori distribution of the parameter. Not all decision problems in practice come to us imbedded in su
An empirical Bayes approach to inferring large-scale gene association networks
MOTIVATION Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis where the sample size is small compared to the number of considered genes. Thi
An Empirical Bayes Approach to Combining and Comparing Estimates of the Value of a Statistical Life for Environmental Policy Analysis
An empirical Bayes pooling method is used to combine and compare estimates of the value of a statistical life (VSL). The data come from 40 selected studies published between 1974 and 2002, containing 197 VSL estimates. The estimated composite distribution of empirical Bayes adjus
An Empirical Bayes Approach to Robust Variance Estimation: A Statistical Proposal for Quantitative Medical Image Testing
The current standard for measuring tumor response using X-ray, CT and MRI is based on the response evaluation criterion in solid tumors (RECIST) which, while providing simplifications over previous (WHO) 2-D methods, stipulate four response categories: CR (complete response), PR