Small Area Estimation
Wiley-Interscience (Hersteller)
978-0-471-72218-2 (ISBN)
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An accessible introduction to indirect estimation methods, both traditional and model-based. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation.
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
J. N. K. RAO, PhD, is Professor Emeritus and Distinguished Research Professor in the School of Mathematics and Statistics, Carleton University, Ottawa, Canada. He is an editorial advisor for the Wiley Series in Survey Methodology.
List of Figures. 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.
| Erscheint lt. Verlag | 1.2.2005 |
|---|---|
| Reihe/Serie | Wiley Series in Survey Methodology |
| Zusatzinfo | Tables: 20 B&W, 0 Color; Graphs: 4 B&W, 0 Color |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| ISBN-10 | 0-471-72218-9 / 0471722189 |
| ISBN-13 | 978-0-471-72218-2 / 9780471722182 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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