Small Area Estimation (Hardcover, 2, Revised)

· 제목 : Small Area Estimation (Hardcover, 2, Revised) 
· 분류 : 외국도서 > 과학/수학/생태 > 수학 > 확률과 통계 > 일반
· ISBN : 9781118735787
· 쪽수 : 480쪽
· 출판일 : 2015-08-24

List of Figures xv

List of Tables xvii

Foreword to the First Edition xix

Preface to the Second Edition xxiii

Preface to the First Edition xxvii

1 *Introduction 1

1.1 What is a Small Area? 1

1.2 Demand for Small Area Statistics, 3

1.3 Traditional Indirect Estimators, 4

1.4 Small Area Models, 4

1.5 Model-Based Estimation, 5

1.6 Some Examples, 6

2 Direct Domain Estimation 9

2.1 Introduction, 9

2.2 Design-Based Approach, 10

2.3 Estimation of Totals, 11

2.4 Domain Estimation, 16

2.5 Modified GREG Estimator, 21

2.6 Design Issues, 23

2.7 *Optimal Sample Allocation for Planned Domains, 26

2.8 Proofs, 32

3 Indirect Domain Estimation 35

3.1 Introduction, 35

3.2 Synthetic Estimation, 36

3.3 Composite Estimation, 57

3.4.1 Common Weight, 63

3.5 Proofs, 71

4 Small Area Models 75

4.1 Introduction, 75

4.2 Basic Area Level Model, 76

4.3 Basic Unit Level Model, 78

4.4 Extensions: Area Level Models, 81

4.5 Extensions: Unit Level Models, 88

4.6 Generalized Linear Mixed Models, 92

5 Empirical Best Linear Unbiased Prediction (EBLUP): Theory 97

5.1 Introduction, 97

5.2 General Linear Mixed Model, 98

5.3 Block Diagonal Covariance Structure, 108

5.4 *Model Identification and Checking, 111

5.5 *Software, 118

6 Empirical Best Linear Unbiased Prediction (EBLUP): Basic Area Level Model 123

6.1 EBLUP Estimation, 123

6.2 MSE Estimation, 136

6.3 *Robust Estimation in the Presence of Outliers, 146

6.4 *Practical Issues, 148

6.5 *Software, 169

7 Basic Unit Level Model 173

7.1 EBLUP Estimation, 173

7.2 MSE Estimation, 179

7.3 *Applications, 186

7.4 *Outlier Robust EBLUP Estimation, 193

7.5 *M-Quantile Regression, 200

7.6 *Practical Issues, 205

7.7 *Software, 227

7.8 *Proofs, 231

8 EBLUP: Extensions 235

8.1 *Multivariate Fay–Herriot Model, 235

8.2 Correlated Sampling Errors, 237

8.3 Time Series and Cross-Sectional Models, 240

8.4 *Spatial Models, 248

8.5 *Two-Fold Subarea Level Models, 251

8.6 *Multivariate Nested Error Regression Model, 253

8.7 Two-Fold Nested Error Regression Model, 254

8.8 *Two-Level Model, 259

8.9 *Models for Multinomial Counts, 261

8.10 *EBLUP for Vectors of Area Proportions, 262

8.11 *Software, 264

9 Empirical Bayes (EB) Method 269

9.1 Introduction, 269

9.2 Basic Area Level Model, 270

9.3 Linear Mixed Models, 287

9.4 *EB Estimation of General Finite Population Parameters, 289

9.5 Binary Data, 298

9.6 Disease Mapping, 308

9.7 *Design-Weighted EB Estimation: Exponential Family Models, 313

9.8 Triple-Goal Estimation, 315

9.9 Empirical Linear Bayes, 319

9.10 Constrained LB, 324

9.11 *Software, 325

9.12 Proofs, 330

10 Hierarchical Bayes (HB) Method 333

10.1 Introduction, 333

10.2 MCMC Methods, 335

10.3 Basic Area Level Model, 347

10.4 *Unmatched Sampling and Linking Area Level Models, 356

10.5 Basic Unit Level Model, 362

10.6 General ANOVA Model, 368

10.7 *HB Estimation of General Finite Population Parameters, 369

10.8 Two-Level Models, 374

10.9 Time Series and Cross-Sectional Models, 377

10.10 Multivariate Models, 381

10.11 Disease Mapping Models, 383

10.12 *Two-Part Nested Error Model, 388

10.13 Binary Data, 389

10.14 *Missing Binary Data, 397

10.15 Natural Exponential Family Models, 398

10.16 Constrained HB, 399

10.17 *Approximate HB Inference and Data Cloning, 400

10.18 Proofs, 402

References 405

Author Index 431

Subject Index 437