[R] Pearson residuals in quasi family

[MUGGEO VITO]

Hi all,
This is a very silly question or something escapes me:
Let obj a simple gam poisson model. Let

>obj<-gam(....,family=poisson)
>obj1<-update(obj, family=quasi(link="log", var="mu"))

>From summary.glm(obj1) the dispersion parameter is estimated 1.165; In fact
it is:

> (predict(obj1, se.fit=T)$se.fit[1:5]/predict(obj, se.fit=T)$se.fit[1:5])^2
        4        5        6        7        8
 1.165767 1.165767 1.165767 1.165767 1.165767

The standard errors of the fitted values are greater in the quasi-Lik
approach, of course.
Because of this, it's expected that the pearson residuals are smaller in the
quasi-Lik, approach; but

> residuals(obj, type="pearson")[1:5]-residuals(obj1, type="pearson")[1:5]
 4 5 6 7 8
 0 0 0 0 0

That is
resid(obj1, type="pearson")!=resid(obj1, "response")/(predict(obj1,
se.fit=T)$se.fit

Am I wrong or is there any problem?

Thanks for your attention,
best,
vito

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