Re: [R] maximum likelihood method to fit a model

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Wed, 23 Jul 2008 11:35:33 +0100 (BST)

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

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Received on Wed 23 Jul 2008 - 11:30:27 GMT

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