Bayesian Statistical Modeling with Stan, R, and Python

Kentaro Matsuura ()
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Kentaro Matsuura: HOXO-M Inc.

in Springer Books from Springer

Date: 2022
ISBN: 978-981-19-4755-1
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Chapters in this book:

Ch Chapter 1 Overview of Statistical Modeling

Kentaro Matsuura

Ch Chapter 10 Discrete Parameters

Kentaro Matsuura

Ch Chapter 11 Time Series Data Analysis with State Space Model

Kentaro Matsuura

Ch Chapter 12 Spatial Data Analysis Using Gaussian Markov Random Fields and Gaussian Processes

Kentaro Matsuura

Ch Chapter 13 Usages of MCMC Samples from Posterior and Predictive Distributions

Kentaro Matsuura

Ch Chapter 14 Other Advanced Topics

Kentaro Matsuura

Ch Chapter 2 Overview of Bayesian Inference

Kentaro Matsuura

Ch Chapter 3 Overview of Stan

Kentaro Matsuura

Ch Chapter 4 Simple Linear Regression

Kentaro Matsuura

Ch Chapter 5 Basic Regressions and Model Checking

Kentaro Matsuura

Ch Chapter 6 Introduction of Probability Distributions

Kentaro Matsuura

Ch Chapter 7 Issues of Regression

Kentaro Matsuura

Ch Chapter 8 Hierarchical Model

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Ch Chapter 9 How to Improve MCMC ConvergenceMCMC convergence

Kentaro Matsuura

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DOI: 10.1007/978-981-19-4755-1

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