Displaying 6 results from an estimated 6 matches for "wedderburn".
2005 Jun 16
1
mu^2(1-mu)^2 variance function for GLM
Dear list,
I'm trying to mimic the analysis of Wedderburn (1974) as cited by
McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on
barley example, and the data is available in the `faraway' package.
Wedderburn suggested using the variance function mu^2(1-mu)^2. This
variance function isn't readily available in R's `quasi'...
2015 Jun 25
1
Estimating overdispersion when using glm for count and binomial data
Dear All
I recently proposed a simple modification to Wedderburn's 1974 estimate
of overdispersion for count and binomial data, which is used in glm for
the quasipoisson and quasibinomial families (see the reference below).
Although my motivation for the modification arose from considering
sparse data, it will be almost identical to Wedderburn's esti...
2008 Mar 17
1
generalized linear mixed models with a beta distribution [Sec=Unclassified]
...otal N (these do not have to be integers)
but remember to use prior weights of 1/N and estimate the
over-dispersion parameter. If you use the ratio, r, directly with a
binomial total of 1 then the prior weights are simply 1 and can be
ignored. This quasi-likelihood approach for a ratio was given by
Wedderburn (1974) (see McCullagh and Nelder, 1989, Sec 9.2.4). BTW
random effects with a beta distribution included in the linear predictor
via a link function such as the logit can be fitted as a HGLM
(Hierarchical Generalized Linear Model)(Lee and Nelder, 1996, 2001) for
binomial data (i.e. considered binom...
2015 Jun 26
0
Estimating overdispersion when using glm for count and binomial data
..., I think it
> is much more likely to find a home in an add-on package such as aods3
> or glm2 than in base R ...
Thanks for these suggestions Ben - Simon Wood has also been in touch,
and plans to put it into mgcv
David Fletcher
Original post:
I recently proposed a simple modification to Wedderburn's 1974 estimate
of overdispersion for count and binomial data, which is used in glm for
the quasipoisson and quasibinomial families (see the reference below).
The modification is very simple and would take at most a couple of lines
of code. The reference below gives details regarding its as...
1999 Apr 19
1
Algorithm used by glm, family=binomial?
Does anyone know what algorithm R uses in glm, family=binomial (i.e. a
logit model)?
I assume that it's in the source somewhere, but I wasn't able to find
it. I'd like to know
what file it's in (in a unix distribution of R).
Thanks for your help.
---------------------------
Barnet Wagman
wagman at enteract.com
1361 N. Hoyne, 2nd floor
Chicago, IL 60622
773-645-8369
2004 Mar 16
2
glm questions
Greetings, everybody. Can I ask some glm questions?
1. How do you find out -2*lnL(saturated model)?
In the output from glm, I find:
Null deviance: which I think is -2[lnL(null) - lnL(saturated)]
Residual deviance: -2[lnL(fitted) - lnL(saturated)]
The Null model is the one that includes the constant only (plus offset
if specified). Right?
I can use the Null and Residual deviance to