[R] GLM weights for the Poisson family

[Rolf Turner]

On 04/02/14 20:12, IamRandom wrote:

> I am running a simple example of GLM.  If I include weights when
> family="poisson" then the weights are calculated iteratively and
> $weights and $prior.weights return different values.  The $prior.weights
> are what I supplied and $weights are the "posterior" weights of the
> IWLS.  If I include weights with family="gaussian" then the weights are
> static and $weights and $prior.weights return the same values; it seems
> to ignore IWLS algorithm procedure.  I really want the family="poisson"
> to behave like the family="gaussian" and use the static weights.  Thoughts?

As far as I understand things, your desideratum makes no sense.  The 
prior weights and the just-plain-weights are very different creatures.
The reason they wind up being the same for the gaussian family is that 
for the gaussian family the likelihood is maximized by least squares; 
there is no need for iteration or for re-weighting.

The poisson family cannot behave like the gaussian family because for 
the poisson family (or any family *other* than gaussian) iteration is 
necessary in order to maximize the likelihood.

You might get some insight into what's going on if you were to read 
Annette Dobson's book "An Introduction to Generalized Linear Models"
(Chapman and Hall, 1990).

cheers,

Rolf Turner