Recent Advances in Linear Models and Related Areas (PDF)
The theory of linear models and regression analysis plays an essential role in the development of methods for the statistical modelling of data.
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The theory of linear models and regression analysis plays an essential role in the development of methods for the statistical modelling of data.
The book presents the most recent developments in the theory and applications of linear models and related areas of active research. The contributions include topics such as boosting, Cox regression models, cluster analysis, design of experiments, feasible generalized least squares, information theory, matrix theory, measurement error models, missing data models, mixture models, panel data models, penalized least squares, prediction, regression calibration, spatial models and time series models.
Several contributions illustrate applications in biomedical research, economics, finance, genetic epidemiology and medicine.
- Autoren: Christian Heumann , Shalabh
- 2008, 2008, 445 Seiten, Englisch
- Herausgegeben: Shalabh, Christian Heumann
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3790820644
- ISBN-13: 9783790820645
- Erscheinungsdatum: 11.07.2008
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 4.72 MB
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“This is a festschrift for Professor Helge Toutenburg on the occasion of his 65th birthday. … In addition, the general mixture model class is presented and several special cases are discussed … . This great variety of topics, as well as the very clear style of the presentation makes a pleasant reading. Overall, if I had to recommend a good book on recent advances in the study of linear models, I would choose this one.” (J. A. Pardo, Statistical Papers, Vol. 52, 2011)
“This edited volume attempts to present some recent developments in linear models and related areas. … This collection comprises 24 papers to honor the contributions of Helge Toutenburg, an accomplished and established statistician, on his 65th birthday. … This volume will be useful and of interest to the intended audience—experienced researchers as well as practitioners in the field of linear models.” (Technometrics, Vol. 51 (2), May, 2009)
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