[R] maximum likelihood method to fit a model

[Prof Brian Ripley]

On Wed, 23 Jul 2008, silvia narduzzi wrote:

> Dear R users,

> I use the glm() function to fit a generalized linear model with gamma 
> distribution function and log link. I have read in the help page that 
> the default method used by R is "glm.fit" (iteratively reweighted least 
> squares, IWLS). Is it possible to use maximum likelihood method?

IRLS does implement maximum likelihood for the coefficients of the linear 
predictor.  glm() does not estimate the gamma shape (summary.glm does, 
though), and MASS (the book and packages) discusses how to find the MLE of 
the shape.

See

library(MASS)
?gamma.shape


> Silvia Narduzzi
> Dipartimento di Epidemiologia
> ASL RM E
> Via di S. Costanza, 53
> 00198 Roma
> Tel  +39 06 83060461
> Mail  narduzzi at asplazio.it

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595