Bayesian hierarchical models : with applications using R / Peter D. Congdon.

Format:

Book

Author/Creator:

Congdon, P.

Contributor:

Taylor & Francis eBooks.

Standardized Title:

Applied Bayesian hierarchical methods

Language:

English

Subjects (All):

Bayesian statistical decision theory.

Physical Description:

1 online resource (593 pages)

polychrome

Edition:

Second edition.

Place of Publication:

Boca Raton, FL : CRC Press, [2020]

System Details:

text file

Biography/History:

Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.

Contents:

Chapter 1 Bayesian Methods for Complex Data: Estimation and Inference; Chapter 2 Computing Options and Strategies; Chapter 3 Model Fit, Comparison, and Checking; Chapter 4 Borrowing Strength Estimation for Exchangeable Units; Chapter 5 Structured Priors Recognizing Similarity over Time and Space; Chapter 6 Regression Techniques using Hierarchical Priors; Chapter 7 Multilevel Models; Chapter 8 Regression for Causal Effects with Observational Data; Chapter 9 Hierarchical Models for Panel Data; Chapter 10 Multivariate Priors, with a Focus on Factor and Structural Equation Models; Chapter 11 Survival and Event History Models; Chapter 12 Hierarchical Methods for Nonlinear Regression.

Notes:

Electronic reproduction. London Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on October 31, 2019).

Other Format:

Print version: Congdon, Peter D. Bayesian Hierarchical Models : With Applications Using R, Second Edition

ISBN:

9781498785914

1498785913

9780429113352

0429113358

9780429532900

0429532903

9780429547607

0429547609

Publisher Number:

99982426577

Access Restriction:

Restricted for use by site license.