Let us look at a piece of the relevant code from "logistf" package:
iter <- iter + 1
XW2 <- crossprod(x, diag(pi * (1 - pi))^0.5)
Fisher <- crossprod(t(XW2))
covs <- solve(Fisher)
H <- crossprod(XW2, covs) %*% XW2
if (firth)
U.star <- crossprod(x, y - pi + diag(H) * (0.5 -
pi))
else U.star <- crossprod(x, y - pi)
delta <- as.vector(covs %*% U.star)
mx <- max(abs(delta))/maxstep
if (mx > 1)
delta <- delta/mx
First, note that this is inside an iterative loop. The Fisher information
matrix is first formed, and then it is inverted to get `covs'. This is where
it can get troublesome. It is very likely in your case that the `Fisher'
information matrix is ill-conditioned, and hence `covs' cannot be computed.
Consequently, the steplength `delta' for the Newton method cannot be
determined.
Ravi.
____________________________________________________________________
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
----- Original Message -----
From: xiaoyan yu <xiaoyan...@gmail.com>
Date: Tuesday, March 9, 2010 11:26 am
Subject: [R] penalized maximum likelihood estimation and logistf
To: r-help@r-project.org
> Hi, I got two questions and would really appreciate any help from here.
> First, is the penalized maximum likelihood estimation(Firth Type Estimation)
> only fit for binary response (0,1 or TRUE, FALSE)? Can it be applied
> to
> multinomial logistic regression?
> If yes, what's the formula for LL and U(beta_i)? Can someone point
> me to
> the right reference?
> Second, when I used *logistf *on a dataset with binary response, I
> got the
> following error msg:
> "Error in if (mx > 1) delta <- delta/mx :
> missing value where TRUE/FALSE needed"
>
> What does this msg mean? does it mean the dataset includes missing response?
> I checked my dataset several times and didn't find anything other
> than TRUE
> or FALSE for the response. Please shed light on this.
>
> Thanks,
> Xiaoyan
>
> [[alternative HTML version deleted]]
>
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> R-help@r-project.org mailing list
>
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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