Recent Advances in Linear Models and Related Areas

Essays in Honour of Helge Toutenburg

  • Shalabh
  • Christian Heumann

Table of contents

  1. Front Matter
    Pages I-XV
  2. Hyang Mi Kim, A. K. Md. Ehsanes Saleh
    Pages 79-93
  3. Götz Trenkler, Dietrich Trenkler
    Pages 95-104
  4. Huaizhen Qin, Alan T. K. Wan, Guohua Zou
    Pages 135-163
  5. Anoop Chaturvedi, Suchita Kesarwani, Ram Chandra
    Pages 181-204
  6. Bettina Grün, Friedrich Leisch
    Pages 205-230
  7. Changli He, Hans Malmsten, Timo Teräsvirta
    Pages 231-251
  8. Jörg Drechsler, Susanne Rässler
    Pages 341-355
  9. Rashi Gupta, Panu Somervuo, Sangita Kulathinal, Petri Auvinen
    Pages 389-400
  10. Thomas Nittner
    Pages 427-439
  11. Back Matter
    Pages 441-445

About this book


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.


Econometrics Estimator Fitting Generalized linear model Linear Models Logistic Regression Matrix Matrix Theory Regression Regression analysis Time series Variance cluster analysis correlation linear regression

Authors and affiliations

  • Shalabh
    • 1
  • Christian Heumann
    • 2
  1. 1.Department of Mathematics & StatisticsIndian Institute of Technology KanpurKanpurIndia
  2. 2.Institute of StatisticsLudwig-Maximilians-University MunichMunichGermany

Bibliographic information

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