SMALL AREA ESTIMATION
商品資訊
ISBN13：9780471413745
出版社：JOHN WILEY & SONS;LTD
作者：RAO
出版日：2003/01/09
裝訂／頁數：精裝／344頁
商品簡介
- Uses a basic area-level linear model to illustrate the methods
- Presents the various extensions including binary response data through generalized linear models and time series data through linear models that combine cross-sectional and time series features
- Provides recent applications of SAE including several in U.S. Federal programs
- Offers a comprehensive discussion of the design issues that impact SAE
作者簡介
目次
List of Tables.
Foreword.
Preface.
1. Introduction.
What is a Small Area?
Demand for Small Area Statistics.
Traditional Indirect Estimators.
Small Area Models.
Model-Based Estimation.
Some Examples.
2. Direct Domain Estimation.
Introduction.
Design-based Approach.
Estimation of Totals.
Domain Estimation.
Modified Direct Estimators.
Design Issues.
Proofs.
3. Traditional Demographic Methods.
Introduction.
Symptomatic Accounting Techniques.
Regression Symptomatic Procedures.
Dual-system Estimation of Total Population.
Derivation of Average MSEs.
4. Indirect Domain Estimation.
Introduction.
Synthetic Estimation.
Composite Estimation.
James-Stein Method.
Proofs.
5. Small Area Models.
Introduction.
Basic Area Level (Type A) Mode l.
Basic Unit Level (Type B) Model.
Extensions: Type A Models.
Extensions: Type B Models.
Generalized Linear Mixed Models.
6. Empirical Best Linear Unbiased Prediction: Theory.
Introduction.
General Linear Mixed Model.
Block Diagonal Covariance Structure.
Proofs.
7. EBLUP: Basic Models.
Basic Area Level Model.
Basic Unit Level Model.
8. EBLUP: Extensions.
Multivariate Fay-Herriot Model.
Correlated Sampling Errors.
Time Series and Cross-sectional Models.
Spatial Models.
Multivariate Nested Error Regression Model.
Random Error Variances Linear Model.
Two-fold Nested Error Regression Model.
Two-level Model.
9. Empirical Bayes (EB) Method.
Introduction.
Basic Area Level Model.
Linear Mixed Models.
Binary Data.
Disease Mapping.
Triple-goal Estimation.
Empirical Linear Bayes.
Constrained LB.
Proofs.
10. Hierarchical Bayes (HB) Method.
Introduction.
MCMC Methods.
Basic Area Level Model.
Unmatched Sampling and Linking Area Level Models.
Basic Unit Level Model.
General ANOVA Model.
Two-level Models.
Time Series and Cross-sectional Models.
Multivariate Models.
Disease Mapping Models.
Binary Data.
Exponential Family Models.
Constrained HB.
Proofs.
References.
Author Index.
Subject Index.
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