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Bayesian and Frequentist Regression Methods

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Cover of 'Bayesian and Frequentist Regression Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction and Motivating Examples
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    Chapter 2 Frequentist Inference
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    Chapter 3 Bayesian Inference
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    Chapter 4 Hypothesis Testing and Variable Selection
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    Chapter 5 Linear Models
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    Chapter 6 General Regression Models
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    Chapter 7 Binary Data Models
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    Chapter 8 Linear Models
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    Chapter 9 General Regression Models
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    Chapter 10 Preliminaries for Nonparametric Regression
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    Chapter 11 Spline and Kernel Methods
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    Chapter 12 Nonparametric Regression with Multiple Predictors
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    Chapter 13 Differentiation of Matrix Expressions
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    Chapter 14 Matrix Results
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    Chapter 15 Some Linear Algebra
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    Chapter 16 Probability Distributions and Generating Functions
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    Chapter 17 Functions of Normal Random Variables
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    Chapter 18 Some Results from Classical Statistics
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    Chapter 19 Basic Large Sample Theory
Attention for Chapter 10: Preliminaries for Nonparametric Regression
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