| Description |
1 online resource (522 pages) |
| Contents |
Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; List of Figures; List of Tables; Preface; Acknowledgments; List of Abbreviations; 1: Introduction; 1.1 Introduction; 1.2 Main Aims of the Book; 1.3 Guide for the Reader; 1.4 Concluding Remarks; 2: Small Area Estimation; 2.1 Introduction; 2.2 Small Area Estimation; 2.2.1 Concept of Small Area; 2.2.2 Advantages of SAE; 2.2.3 Why SAE Techniques?; 2.2.4 Applications of SAE; 2.3 Approaches to SAE; 2.4 Direct Estimation; 2.4.1 H-T Estimator; 2.4.2 Generalized Regression Estimator; 2.4.3 Modified Direct Estimator |
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2.4.4 Design-Based Model-Assisted Estimators2.4.5 A Comparison of Direct Estimators; 2.5 Concluding Remarks; 3: Indirect Estimation: Statistical Approaches; 3.1 Introduction; 3.2 Implicit Models Approach; 3.2.1 Synthetic Estimation; 3.2.2 Composite Estimation; 3.2.3 Demographic Estimation; 3.2.4 Comparison of Various Implicit Models-Based Indirect Estimation; 3.3 Explicit Models Approach; 3.3.1 Basic Area Level Model; 3.3.2 Basic Unit Level Model; 3.3.3 Generalized Linear Mixed Model; 3.3.4 Comparison of Various Explicit Models-Based Indirect Estimation |
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3.4 Methods for Estimating Explicit Models3.4.1 EBLUP Approach; 3.4.2 EB Approach; 3.4.3 HB Approach; 3.4 A Comparison of Three Methods; 3.5 Concluding Remarks; 4: Indirect Estimation: Geographic Approaches; 4.1 Introduction; 4.2 Microsimulation Modeling; 4.2.1 Process of Microsimulation; 4.2.2 Types of Microsimulation Models; 4.2.2.1 Static Microsimulation; 4.2.2.2 Dynamic Microsimulation; 4.2.2.3 Spatial Microsimulation; 4.2.3 Advantages of Microsimulation Modeling; 4.3 Methodologies in Microsimulation Modeling Technology; 4.3.1 Techniques for Creating Spatial Microdata |
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4.3.2 Statistical Data Matching or Fusion4.3.3 Iterative Proportional Fitting; 4.3.4 Repeated Weighting Method; 4.3.5 Reweighting; 4.4 CO Reweighting Approach; 4.4.1 Simulated Annealing Method in CO; 4.4.2 Illustration of CO Process for Hypothetical Data; 4.5 Reweighting: The GREGWT Approach; 4.5.1 Theoretical Setting; 4.5.2 How Does GREGWT Generate New Weights?; 4.5.3 Explicit Numerical Solution for Hypothetical Data; 4.6 Comparison between GREGWT and CO; 4.7 Concluding Remarks; 5: Bayesian Prediction-Based Microdata Simulation; 5.1 Introduction; 5.2 Basic Steps |
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5.3 Bayesian Prediction Theory5.4 Multivariate Model; 5.5 Prior and Posterior Distributions; 5.6 The Linkage Model; 5.7 Prediction for Modeling Unobserved Population Units; 5.8 Concluding Remarks; 6: Microsimulation Modeling Technology for Small Area Estimation; 6.1 Introduction; 6.2 Data Sources and Issues; 6.2.1 Census Data; 6.2.2 Survey Data Sets; 6.3 Microsimulation Modeling Technology-Based Model Specification; 6.3.1 Model Inputs; 6.3.1.1 General Model File; 6.3.1.2 Unit Record Data Files; 6.3.1.3 Benchmark Files; 6.3.1.4 Auxiliary Data Files; 6.3.1.5 GREGWT File |
| Notes |
6.3.2 Generating Small Area Synthetic Weights |
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Print version record |
| Subject |
Small area statistics.
|
|
Statistical machining
|
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Small area statistics
|
| Form |
Electronic book
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| Author |
Harding, Ann
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| ISBN |
9781482260731 |
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1482260735 |
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