Seemingly unrelated regression equations models: estimation and inference
Title Statements
- Full title :Seemingly unrelated regression equations models : estimation and inference / Virendra K. Srivastava, David E.A. Giles.
Edition Statements
- Publication Date:c1987.
Publication Statements
- Publisher(s):Dekker
- Place of Publication:New York
- Language:eng
- Publication Date:c1987.
The Physical Object
- Description:1 online resource (xii, 374 pages) : : illustrations).
Edition Identifiers
- ISBN:9781000105728, 1000105725, 9781003065654, 1003065651
- oclc:on1192411451
- LC Classification:QA276.8
- Dewey Decimal:511.4
Table of Contents
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication Page -- Preface -- Contents -- 1 The Seemingly Unrelated Regression Equations Model -- 1.1 Introduction -- 1.2 The Model -- 1.3 Outline -- Exercises -- References -- 2 The Least Squares Estimator and Its Variants -- 2.1 Introduction -- 2.2 The Ordinary Least Squares and Generalized Least Squares Estimators -- 2.3 The Feasible Generalized Least Squares Estimator -- 2.4 Optimality of Ordinary Least Squares -- 2.5 Simplifications of Feasible Generalized Least Squares -- 2.6 Some Asymptotic Properties -- Exercises
4.3 The Two Equation Model -- 4.4 Efficiency Properties Under Orthogonal Regressors -- 4.5 Efficiency Properties Under Subset Regressors -- 4.6 Efficiency Properties Under Unconstrained Regressors -- 4.7 Some Further Results -- 4.8 The Multi-Equation Model -- Exercises -- References -- 5 Iterative Estimators -- 5.1 Introduction -- 5.2 The Iterative Feasible Generalized Least Squares Estimator -- 5.3 The Iterative Ordinary Least Squares Estimator -- 5.4 The Maximum Likelihood Estimator -- 5.5 Computational Issues -- 5.6 Unbiasedness -- 5.7 Efficiency Properties -- Exercises -- References
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