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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > On applications of Empirical Bayes approaches to the Normal Means problem

## On applications of Empirical Bayes approaches to the Normal Means problemAdd to your list(s) Download to your calendar using vCal - Matthew Stephens (University of Chicago)
- Monday 25 June 2018, 14:00-14:45
- Seminar Room 1, Newton Institute.
If you have a question about this talk, please contact INI IT. STSW04 - Future challenges in statistical scalability The normal means problem is very simple: given normally-distributed observations with known variances and unknown means, estimate the means. That is, given X_j \sim N(\theta_j, \sigma_j^2, estimate \theta_j. A key idea is that one can do better than the maximum likelihood estimates, \hat{\theta}_j= \X_j, in particular by use of appropriate “shrinkage” estimators. One attractive way to perform shrinkage estimation in practice is to use Empirical Bayes methods. That is, to assume that \theta_j are independent and identically distributed from some distribution g that is to be estimated from the data. Then, given such an estimate \hat{g}, the posterior distributions of \theta_j can be computed to perform inference. We call this the “Empirical Bayes Normal Means” (EBNM) problem. This talk is part of the Isaac Newton Institute Seminar Series series. ## This talk is included in these lists:- All CMS events
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