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The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and evenhanded account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the 'uniformly most powerful' approach to testing is contrasted with available decisiontheoretic approaches.
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