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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Autor Corporativo: | |
Otros Autores: | , , |
Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2008.
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Edición: | 3rd extended ed |
Colección: | Springer series in statistics.
Springer eBooks. |
Acceso en línea: | Conectar con la versión electrónica |
Ver en Universidad de Navarra: | https://innopac.unav.es/record=b32746763*spi |
Sumario: | 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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Descripción Física: | XIX, 572 p. |
Formato: | Forma de acceso: World Wide Web. |
ISBN: | 9783540742272 |