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Introduction to Generalized Linear Modelling P.M.E.Altham, Statistical Laboratory, University of Cambridge.
 

Summary: Introduction to Generalized Linear Modelling
P.M.E.Altham, Statistical Laboratory, University of Cambridge.
August 20, 2010
1 Introduction
Preliminary statement. When I first wrote my lecture notes for the Part II course, Sarah Shea­
Simonds very kindly typed the core notes in TeX, and I added to them bit by bit, again in TeX.
However, my style was still rather like a telegram, partly as I was trying to save on paper. Now
that I am retired, I have time to retype the notes in LaTeX. I have tried to make the style rather
more `flowing', and have included more various graphs, exercises, Tripos questions and solutions.
This editing process is quite enjoyable but rather slow. I'll put the revisions on my webpage from
time to time, and of course would appreciate comments and suggestions. Special thanks are due to
Professor Yuri Suhov for his comments and suggestions.
There are already several excellent books on this topic. For example McCullagh and Nelder(1989)
have written the classic research monograph, and Aitkin et al. (1989) have an invaluable intro-
duction to the pioneering software GLIM. Although I was very glad to learn a great deal by using
GLIM, that particular software was superseded some years ago by excellent and powerful languages
such as S-Plus and R.
Students will naturally gain a much deeper understanding of the theory by putting it into practice
on real (if small) datasets. An excellent text book to help them to do this in Splus and/or R is
the one by Venables and Ripley (2002), particularly their Chapters 6 and 7.

  

Source: Altham, Pat - Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge

 

Collections: Mathematics