책 이미지
책 정보
· 분류 : 외국도서 > 과학/수학/생태 > 수학 > 확률과 통계 > 일반
· ISBN : 9781439840955
· 쪽수 : 675쪽
· 출판일 : 2013-11-07
목차
FUNDAMENTALS OF BAYESIAN INFERENCE
Probability and Inference
Single-Parameter Models
Introduction to Multiparameter Models
Asymptotics and Connections to Non-Bayesian Approaches
Hierarchical Models
FUNDAMENTALS OF BAYESIAN DATA ANALYSIS
Model Checking
Evaluating, Comparing, and Expanding Models
Modeling Accounting for Data Collection
Decision Analysis
ADVANCED COMPUTATION
Introduction to Bayesian Computation
Basics of Markov Chain Simulation
Computationally Efficient Markov Chain Simulation
Modal and Distributional Approximations
REGRESSION MODELS
Introduction to Regression Models
Hierarchical Linear Models
Generalized Linear Models
Models for Robust Inference
Models for Missing Data
NONLINEAR AND NONPARAMETRIC MODELS
Parametric Nonlinear Models
Basic Function Models
Gaussian Process Models
Finite Mixture Models
Dirichlet Process Models
APPENDICES
A: Standard Probability Distributions
B: Outline of Proofs of Asymptotic Theorems
C: Computation in R and Stan
Bibliographic Notes and Exercises appear at the end of each chapter.
