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20779
2011 Mar 30
2
glm: modelling zeros as binary and non-zeroes as coming from a continuous distribution
...eros separately and then bring them together by simulation. I can
do this, but it makes it difficult to assess the significance of
regression coefficients wrt to zero and each other.
Another solution I have been pointed at is in SAS:
http://listserv.uga.edu/cgi-bin/wa?A2=ind0805A&L=sas-l&P=R20779,
where they use NLMIXED (with only fixed effects) to specify their own
log-likelihood function.
I'm wondering if there's any way to do the same in R (lme can't deal
with this, as far as I'm aware).
Finally, I'm wondering whether anyone has experience with the COZIGAM
package -...
2011 Sep 14
0
Convert SAS NLMIXED code for zero-inflated gamma regression to R
...e
ll = log(1 - p_yEQ0)
- lgamma(theta) + (theta-1)*log(y) - theta*log(r) - y/r;
model y ~ general(ll);
predict (1 - p_yEQ0)*mu out=expect_zig;
predict r out=shape;
estimate "scale" theta;
run;
From: http://listserv.uga.edu/cgi-bin/wa?A2=ind0805A&L=sas-l&P=R20779
Best,
Mikhail
PS. I cross-posted this to stackoverflow under R and SAS - apologies if
you're reading this twice...
==
Mikhail Spivakov, PhD
European Bioinformatics Institute
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