Linear Models and Generalizations : Least Squares and Alternatives

Thebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in o...

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Auteurs principaux: Rao, Calyampudi Radhakrishna, 1920-2023, mathématicien, Toutenburg, Helge (Auteur), Heumann, Christian (Auteur), Shalabh (Auteur)
Drugi avtorji: Schomaker, Michael (Collaborateur)
Format: Livre numérique
Jezik:Anglais
Izdano: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Izdaja:Version électronique de la troisième édition augmentée.
Serija:Springer Series in Statistics
Teme:
Online dostop:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Sporočilo: L'impression du document génère 582 p.
Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Linear Models and Generalizations, Texte imprimé, 9783540842224
• Linear models and generalizations, least squares and alternatives, C. Radhakrishna Rao ... [et al.], Third extended edition, 2008, Berlin, Springer, 1 vol. (XIX-570 p.), Springer series in statistics, 3-540-74226-3
• Linear models and generalizations, least squares and alternatives, C. Radhakrishna Rao ... [et al.], Third extended edition, 2008, Berlin, Springer, 1 vol. (XIX-570 p.), Springer series in statistics, 3-540-74226-3
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245 1 0 |a Linear Models and Generalizations :  |b Least Squares and Alternatives   |c C. Radhakrishna Rao, Helge Toutenburg, Shalabh, Christian Heumann ; with contributions by Michael Schomaker. 
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520 |a Thebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and o?ers a selectionofclassicalandmodernalgebraicresultsthatareusefulinresearch work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de?niteness ofmatrices,especially forthe di?erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the ?rst time. We have attempted to provide a uni?ed theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss fu- tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and a variety of practical applications will be useful not only to students but also to researchers and consultants in statistics 
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