Bayesian data analysis. (2013)

• Record Type: Book
• Further Information: Note: Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin.
• Authors: Gelman, Andrew
• Contents: 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.
• Publisher Details: Place of publication not identified : CRC Press
• Publication Date: 2013
• Extent: 1 online resource, illustrations
• Subjects: 519.542; Bayesian statistical decision theory; MATHEMATICS / Probability & Statistics / General
• Languages: English
• ISBNs: 9781439898222; 1439898227
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.