I. Introduction to the Population-Sample Decomposition Approach.- I.1 The linear statistical model.- I.2 Minimum distance parameters subject to minimal model assumptions.- II. The Estimation of Linear Relations; The Sample Part of PSD.- II.1 Method of moments and asymptotic distribution theory.- II.2 Asymptotic estimation of covariance functions.- III. Principal Relations.- III.1 Basic formulation of the principal relations.- III.2 The distance matrix Q.- III.3 Simultaneous equations systems.- III.4 Seemingly unrelated regressions.- III.5 Restricted seemingly unrelated regressions.- III.6 Canonical correlation analysis.- IV. Principal Factors.- IV.1 Basic formulation of principal factors.- IV.2 Principal relations versus principal factors.- IV. 3 Principal components analysis.- V. Goodness-of-Fit Measures.- V. 1 Coefficients of multiple correlation and angles between random vectors.- V.2 Coefficients of linear association for principal relations and principal factors.- V.3 Coefficients of linear association for simultaneous equations systems.- V.4 Coefficients of linear association for seemingly unrelated regressions.- VI. Review.- VI.1 A schematic representation of the parameters.- VI.2 List of notation and summary of results.- VII. Computational Aspects of the Population-Sample Decomposition.- VII.1 Fourth-order central moments.- VII.2 Pre- and post-multiplication of V by the gradient matrix.- VII.3 The PSD method in practice.- Preliminaries on matrix algebra.- References.- Author Index.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -I. Introduction to the Population-Sample Decomposition Approach.- I.1 The linear statistical model.- I.2 Minimum distance parameters subject to minimal model assumptions.- II. The Estimation of Linear Relations; The Sample Part of PSD.- II.1 Method of moments and asymptotic distribution theory.- II.2 Asymptotic estimation of covariance functions.- III. Principal Relations.- III.1 Basic formulation of the principal relations.- III.2 The distance matrix Q.- III.3 Simultaneous equations systems.- III.4 Seemingly unrelated regressions.- III.5 Restricted seemingly unrelated regressions.- III.6 Canonical correlation analysis.- IV. Principal Factors.- IV.1 Basic formulation of principal factors.- IV.2 Principal relations versus principal factors.- IV. 3 Principal components analysis.- V. Goodness-of-Fit Measures.- V. 1 Coefficients of multiple correlation and angles between random vectors.- V.2 Coefficients of linear association for principal relations and principal factors.- V.3 Coefficients of linear association for simultaneous equations systems.- V.4 Coefficients of linear association for seemingly unrelated regressions.- VI. Review.- VI.1 A schematic representation of the parameters.- VI.2 List of notation and summary of results.- VII. Computational Aspects of the Population-Sample Decomposition.- VII.1 Fourth-order central moments.- VII.2 Pre- and post-multiplication of V by the gradient matrix.- VII.3 The PSD method in practice.- Preliminaries on matrix algebra.- References.- Author Index. 256 pp. Englisch. Bestandsnummer des Verkäufers 9789401081474
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. I. Introduction to the Population-Sample Decomposition Approach.- I.1 The linear statistical model.- I.2 Minimum distance parameters subject to minimal model assumptions.- II. The Estimation of Linear Relations The Sample Part of PSD.- II.1 Method of momen. Bestandsnummer des Verkäufers 5834706
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -I. Introduction to the Population-Sample Decomposition Approach.- I.1 The linear statistical model.- I.2 Minimum distance parameters subject to minimal model assumptions.- II. The Estimation of Linear Relations; The Sample Part of PSD.- II.1 Method of moments and asymptotic distribution theory.- II.2 Asymptotic estimation of covariance functions.- III. Principal Relations.- III.1 Basic formulation of the principal relations.- III.2 The distance matrix Q.- III.3 Simultaneous equations systems.- III.4 Seemingly unrelated regressions.- III.5 Restricted seemingly unrelated regressions.- III.6 Canonical correlation analysis.- IV. Principal Factors.- IV.1 Basic formulation of principal factors.- IV.2 Principal relations versus principal factors.- IV. 3 Principal components analysis.- V. Goodness-of-Fit Measures.- V. 1 Coefficients of multiple correlation and angles between random vectors.- V.2 Coefficients of linear association for principal relations and principal factors.- V.3 Coefficients of linear association for simultaneous equations systems.- V.4 Coefficients of linear association for seemingly unrelated regressions.- VI. Review.- VI.1 A schematic representation of the parameters.- VI.2 List of notation and summary of results.- VII. Computational Aspects of the Population-Sample Decomposition.- VII.1 Fourth-order central moments.- VII.2 Pre- and post-multiplication of V by the gradient matrix.- VII.3 The PSD method in practice.- Preliminaries on matrix algebra.- References.- Author Index.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 256 pp. Englisch. Bestandsnummer des Verkäufers 9789401081474
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Taschenbuch. Zustand: Neu. The Population-Sample Decomposition Method | A Distribution-Free Estimation Technique for Minimum Distance Parameters | A. M. Wesselman | Taschenbuch | International Studies in Economics and Econometrics | 256 S. | Englisch | 2011 | Springer | EAN 9789401081474 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 105624408
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