On 25 Aug 2020, at 18:40 , peter dalgaard <pdalgd at gmail.com> wrote:
If you don't worry too much about an additive constant, then half the negative squared deviance residuals should do. (Not quite sure how weights factor in. Looks like they are accounted for.)
-pd
On 25 Aug 2020, at 17:33 , John Smith <jswhct at gmail.com> wrote:
Dear R-help,
The function logLik can be used to obtain the maximum log-likelihood value
from a glm object. This is an aggregated value, a summation of individual
log-likelihood values. How do I obtain individual values? In the following
example, I would expect 9 numbers since the response has length 9. I could
write a function to compute the values, but there are lots of
family members in glm, and I am trying not to reinvent wheels. Thanks!
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
data.frame(treatment, outcome, counts) # showing data
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
(ll <- logLik(glm.D93))
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