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After a brief review of elementary statistical theory， the coverage of thesubject matter begins with a detailed treatment of parametric statisticalmodels as motivated by DeFinetti's representation theorem for exchangeablerandom variables （Chapter l）. In addition， Dirichlet processes and othertailfree processes are presented as examples of infinite-dimensional param-eters. Chapter 2 introduces sufficient statistics from both Bayesian andnon-Bayesian viewpoints. Exponential families are discussed here becauseof the important role sufficiency plays in these models. Also， the conceptof iriformation is introduced together with its relationship to sufficiency.A representation theorem is given for general distributions based on suffi-cient statistics. Decision theory is the subject of Chapter 3， which includesdiscussions of admissibility and minimaxity. Section 3.3 presents an ax-iomatic derivation of Bayesian decision theory， including the use of condi-tional probability. Chapter 4 covers hypothe
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