A half-day short course at Manchester
We are announcing a half-day short course on Hierarchical Generalized
Linear Models (HGLM), which will take place in Manchester
Institute for Mathematical Sciences (MIMS), School of Mathematics,
The University of Manchester, on Wednesday 10th May 2006. For
more details, see
http://www.maths.man.ac.uk/mims/events/courses/hglm.html
The course description is also given below.
Title: Hierarchical Generalized Linear Models
Abstract:
Hierarchical Generalized Linear Models (HGLMs) provide a flexible and
efficient framework for modelling non-Normal data in situations when there
may be several sources of error variation. They are defined by extending the
familiar generalized linear models (GLMs) to include additional random terms
in the linear predictor. They include generalized linear mixed models (GLMMs)
as a special case, but do not constrain the additional terms to follow a Normal
distribution and to have an identity link (as in the GLMM). For example, if the
basic generalized linear model is a log-linear model (Poisson distribution and
log link), a more appropriate assumption for the additional random terms might
be a gamma distribution and a log link. HGLMs thus bring a wide range of
models together within a single framework. Each HGLM is made up from two
interlinked generalized linear models, so we have access to a familiar repertoire
of model checking techniques to help determine the appropriate error
distributions and models.
This course will introduce the underlying theory and show examples of situations
where HGLMs can be useful. It will use the GenStat procedures that have been
written by Payne, Lee, Nelder & Noh to implement the methodology, and which
will accompany the forthcoming book on HGLMs by Lee, Nelder & Pawitan
(due in mid 2006).
References:
Lee, Y. & Nelder, J.A. (1996). Hierarchical generalized linear models (with
discussion). J. R. Statist. Soc. B, 58, 619-678.
Lee, Y. & Nelder, J.A. (2001). Hierarchical generalized linear models: a synthesis of
generalised linear models, random-effect models and structured dispersions.
Biometrika, 88, 987-1006.
Lee, Y. & Nelder, J.A. (2006). Double hierarchical generalized linear models (with
discussion). Appl. Statist., 55, 1-29.
Lecturer: Prof Roger Payne (Rothamsted Research & VSN International)
Prof R Payne worked at Rothamsted for 30 years and is now the Chief Science
and Technology Officer at VSN International Ltd (a company part-owned by
Rothamsted). He is the key developer of the GenStat system and has recently
developed procedures in GenStat for HGLMs jointly with Profs John Nelder
and Youngjo Lee.
Time & Date: 14:00 - 17:00 (including 30min break), Wed 10th May 2006
Place: No C.18, Ferranti Building, Sackville Street Campus,
University of Manchester
Target Audiences and Registration:
The course is free of charge. It is mainly for postgraduate students in Statistics
or Applied Statistics, but anyone who is interested is welcome to attend.
Please send an email to Dr Jianxin Pan at [log in to unmask] to
book a place. The maximum number of audiences we can take is about 40.
Please note it is first come first serviced.
Directions:
The Ferranti building is number 20 on the University Campus map at
http://www.maths.man.ac.uk/mims/graphics/campus-map.pdf, and lies within 5
minutes walk of Piccadilly railway station, which hosts mainline services to most
areas of the UK (London, for example, is 2 hours away, and Manchester International
Airport about 20 minutes). Detailed directions are available on the general information
pages at http://www.maths.man.ac.uk/mims/info/directions.html
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Dr Jianxin Pan
Reader in Statistics
School of Mathematics
University of Manchester
PO Box 88, Sackville Street
Manchester M60 1QD
UK
Tel: 0044 161-27-55864
Fax: 0044 161-30-63220
Email: [log in to unmask]
Web page: http://www.ma.man.ac.uk/~jpan/
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