Is there a function that provides the Fisher information matrix for a
generalized linear model? I do not see how to access the off-diagonal
matrix elements of the value returned by glm. (I'm particularly
interested in logistic regression.)
If not, what is a good way to use R to compute Hessians or other partial
derivatives of log likelihoods?
I would appreciate any guidance.
David
_______________________________________
David R. Bickel http://davidbickel.com
Research Scientist
Pioneer Hi-Bred International (DuPont)
Bioinformatics
7200 NW 62nd Ave.; PO Box 184
Johnston, IA 50131-0184
515-334-4739 Tel
515-334-4473 Fax
david.bickel at pioneer.com
This communication is for use by the intended recipient and ...{{dropped}}
David:
I don't have what you want. But if your model is simple (2-parameter,
binomial response, glm with a logit link) I have some code that computes and
plots the loglikelihood surface using contour() and superimposes the
asymptotic 95% confidence ellipse, for comparison with the observed contour
for qchisq(0.95, df=2)/2. And for many datasets the agreement isn't as nice
as you might hope, and that your Hessian might require. (That is, the
actually contour is not elliptical, or if it is its axes may not agree well
with the pseudo-elliptical contour of the observed loglikelihood surface.)
You may be looking for the resulting confidence bounds on the glm fit for
which I also have code that iteratively interrogates the loglikelihood
surface without plotting it.
If any of this is interesting, please send me a note so we won't clog the
bandwidth.
Charles Annis, P.E.
Charles.Annis at StatisticalEngineering.com
phone: 561-352-9699
eFax: 614-455-3265
http://www.StatisticalEngineering.com
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Bickel, David
Sent: Friday, September 29, 2006 1:50 PM
To: r-help at stat.math.ethz.ch
Subject: [R] GLM information matrix
Is there a function that provides the Fisher information matrix for a
generalized linear model? I do not see how to access the off-diagonal
matrix elements of the value returned by glm. (I'm particularly
interested in logistic regression.)
If not, what is a good way to use R to compute Hessians or other partial
derivatives of log likelihoods?
I would appreciate any guidance.
David
_______________________________________
David R. Bickel http://davidbickel.com
Research Scientist
Pioneer Hi-Bred International (DuPont)
Bioinformatics
7200 NW 62nd Ave.; PO Box 184
Johnston, IA 50131-0184
515-334-4739 Tel
515-334-4473 Fax
david.bickel at pioneer.com
This communication is for use by the intended recipient and ...{{dropped}}
______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
look at summary.glm(), probably you're looking for
fit <- glm(..., family = binomial)
# the inverse Fisher Information matrix
summary(fit)$cov.scaled
I hope it helps.
Best,
Dimitris
--
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
Quoting "Bickel, David" <DAVID.BICKEL at pioneer.com>:
> Is there a function that provides the Fisher information matrix for a
> generalized linear model? I do not see how to access the off-diagonal
> matrix elements of the value returned by glm. (I'm particularly
> interested in logistic regression.)
>
> If not, what is a good way to use R to compute Hessians or other partial
> derivatives of log likelihoods?
>
> I would appreciate any guidance.
>
> David
> _______________________________________
> David R. Bickel http://davidbickel.com
> Research Scientist
> Pioneer Hi-Bred International (DuPont)
> Bioinformatics
> 7200 NW 62nd Ave.; PO Box 184
> Johnston, IA 50131-0184
> 515-334-4739 Tel
> 515-334-4473 Fax
> david.bickel at pioneer.com
>
> This communication is for use by the intended recipient and ...{{dropped}}
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm