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Asymptotic Methods in Statistical Decision Theory

Overview of attention for book
Cover of 'Asymptotic Methods in Statistical Decision Theory'

Table of Contents

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    Book Overview
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    Chapter 1 Experiments—Decision Spaces
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    Chapter 2 Some Results from Decision Theory: Deficiencies
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    Chapter 3 Likelihood Ratios and Conical Measures
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    Chapter 4 Some Basic Inequalities
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    Chapter 5 Sufficiency and Insufficiency
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    Chapter 6 Domination, Compactness, Contiguity
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    Chapter 7 Some Limit Theorems
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    Chapter 8 Invariance Properties
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    Chapter 9 Infinitely Divisible, Gaussian, and Poisson Experiments
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    Chapter 10 Asymptotically Gaussian Experiments: Local Theory
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    Chapter 11 Asymptotic Normality—Global
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    Chapter 12 Posterior Distributions and Bayes Solutions
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    Chapter 13 An Approximation Theorem for Certain Sequential Experiments
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    Chapter 14 Approximation by Exponential Families
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    Chapter 15 Sums of Independent Random Variables
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    Chapter 16 Independent Observations
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    Chapter 17 Independent Identically Distributed Observations
Attention for Chapter 13: An Approximation Theorem for Certain Sequential Experiments
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