bookCambridge University Press eBooksAug 5, 2010Closed access

Large-Scale Inference

Stanford University

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Abstract

We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book…

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Topics & keywords

Keywords
  • Frequentist inference
  • Inference
  • Statistical inference
  • Computer science
  • Data science
  • Bayes' theorem
  • Machine learning
  • Bayesian inference
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