This book is primarily concerned with the estimation of regression models with correlated disturbances. Topics discussed include maximum likelihood, test strategies, Kalman filtering, conditional normal distributions, the Cramér-Rao inequality, Cholesky decomposition, missing observations and numerical optimization. A simple geometrical approach is used.
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Vendeur : Antiquariat Bookfarm, Löbnitz, Allemagne
Softcover. 203 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. 3540539018 Sprache: Englisch Gewicht in Gramm: 900. N° de réf. du vendeur 2347845
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Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar3113020169813
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Vendeur : ralfs-buecherkiste, Herzfelde, MOL, Allemagne
Paperback. Etat : Gut. 196 Seiten guter Zustand/ good. Bibl.-Ex. ha1020804 Sprache: Englisch Gewicht in Gramm: 350. N° de réf. du vendeur 130470
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In each chapter of this volume some specific topics in the econometric analysis of time series data are studied. All topics have in common the statistical inference in linear models with correlated disturbances. The main aim of the study is to give a survey of new and old estimation techniques for regression models with disturbances that follow an autoregressive-moving average process. In the final chapter also several test strategies for discriminating between various types of autocorrelation are discussed. In nearly all chapters it is demonstrated how useful the simple geometric interpretation of the well-known ordinary least squares (OLS) method is. By applying these geometric concepts to linear spaces spanned by scalar stochastic variables, it emerges that well-known as well as new results can be derived in a simple geometric manner, sometimes without the limiting restrictions of the usual derivations, e. g. , the conditional normal distribution, the Kalman filter equations and the Cramer-Rao inequality. The outline of the book is as follows. In Chapter 2 attention is paid to a generalization of the well-known first order autocorrelation transformation of a linear regression model with disturbances that follow a first order Markov scheme. Firstly, the appropriate lower triangular transformation matrix is derived for the case that the disturbances follow a moving average process of order q (MA(q'. It turns out that the calculations can be carried out either analytically or in a recursive manner. 212 pp. Englisch. N° de réf. du vendeur 9783540539018
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783540539018_new
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In each chapter of this volume some specific topics in the econometric analysis of time series data are studied. All topics have in common the statistical inference in linear models with correlated disturbances. The main aim of the study is to give a survey. N° de réf. du vendeur 4892973
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 212. N° de réf. du vendeur 2658588807
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 212 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam. N° de réf. du vendeur 51003736
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 212. N° de réf. du vendeur 1858588813
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. reprint edition. 204 pages. 9.61x6.69x0.48 inches. In Stock. N° de réf. du vendeur x-3540539018
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