Bayesian Methods for Finite Population Sampling

Cox, D.R. (Series edited by)/ Reid, N. (Series edited by)/ Isham, Valerie (Series edited by)/ Tibshirani, R.J. (Series edited by)/ Louis, Thomas A. (Series edited by)/ Tong, Howell (Series edited by)/ Keiding, Niels (Series edited by)/ Ghosh, Malay (Author)/ Meeden, Glen (Author)

ISBN 10: 0412987716 / ISBN 13: 9780412987717

Editore: Chapman & Hall, 1997

Riguardo questo articolo

1st edition. 296 pages. 9.00x6.00x0.75 inches. In Stock. Codice articolo __0412987716

Dati bibliografici

Titolo: Bayesian Methods for Finite Population ...

Casa editrice: Chapman & Hall

Data di pubblicazione: 1997

Legatura: Hardcover

Condizione: Brand New

Descrizione articolo

Riassunto:

Assuming a basic knowledge of the frequentist approach to finite population sampling, Bayesian Methods for Finite Population Sampling describes Bayesian and predictive approaches to inferential problems with an emphasis on the likelihood principle. The authors demonstrate that a variety of levels of prior information can be used in survey sampling in a Bayesian manner. Situations considered range from a noninformative Bayesian justification of standard frequentist methods when the only prior information available is the belief in the exchangeability of the units to a full-fledged Bayesian model. Intended primarily for graduate students and researchers in finite population sampling, this book will also be of interest to statisticians who use sampling and lecturers and researchers in general statistics and biostatistics.

Contenuti:

Bayesian Foundations
Notation
Sufficiency
The Sufficiency and Likelihood Principles
A Bayesian Example
Posterior Linearity
Overview
A Noninfromative Bayesian Approach
A Binomial Example
A Characterization of Admissibility
Admissibility of the Sample Mean
Set Estimation
The Polya Urn
The Polya Posterior
Simulating the Polya Posterior
Some Examples
Extensions of the Polya Posterior
Prior Information
Using an Auxiliary Variable
Stratification and Prior Information
Choosing between Experiments
Nonresponse
Some Nonparametric Problems
Linear Interpolation
Empirical Bayes Estimation
Introduction Stepwise Bayes Estimators
Estimation of Stratum Means
Robust Estimation of Stratum Means
Multistage Sampling
Auxiliary Information
Nested Error Regression Models
Hierarchical Bayes Estimation
Introduction
Stepwise Bayes Estimators
Estimation of Stratum Means
Auxiliary Information I
Auxiliary Information II