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A Course in Mathematical Statistics and Large Sample Theory

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Cover of 'A Course in Mathematical Statistics and Large Sample Theory'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Decision Theory
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    Chapter 3 Introduction to General Methods of Estimation
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    Chapter 4 Sufficient Statistics, Exponential Families, and Estimation
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    Chapter 5 Testing Hypotheses
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    Chapter 6 Consistency and Asymptotic Distributions of Statistics
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    Chapter 7 Large Sample Theory of Estimation in Parametric Models
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    Chapter 8 Tests in Parametric and Nonparametric Models
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    Chapter 9 The Nonparametric Bootstrap
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    Chapter 10 Nonparametric Curve Estimation
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    Chapter 11 Edgeworth Expansions and the Bootstrap
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    Chapter 12 Fréchet Means and Nonparametric Inference on Non-Euclidean Geometric Spaces
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    Chapter 13 Multiple Testing and the False Discovery Rate
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    Chapter 14 Markov Chain Monte Carlo (MCMC) Simulation and Bayes Theory
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    Chapter 15 Miscellaneous Topics
Attention for Chapter 13: Multiple Testing and the False Discovery Rate
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