`poisson` summary fails with `weights` parameter

[whatever]

weights parameter breaks the use of the summary method.

Example:

#poisson
obj <- zelig(treat~black+married, model = "poisson",  robust=list(method="weave"), data = lalonde)
summary(obj)
exp(1.956)#7.070986 quite different results
#In my data, the results are even more striking when including a covariate 
#(as for "married" here, my covariate is a binary variable and setx is taking the "mean", taking the mode gives even more different results)


#SECOND PROBLEM: fitting poisson model with robust standard error and weight 
length(lalonde$treat)
#creation of false weights 
lalonde$w=c(rep(1,300),rep(2,314))
#fit
obj <- zelig(treat~black+married, model = "poisson",  robust=list(method="weave"), weights="w",data = lalonde)
summary(obj)
#ERROR message:
#Error in model.frame.default(formula = treat ~ black + married, data = lalonde,  : 
#variable lengths differ (found for '(weights)')


#I need to do that with imputed data so that it should work with the following syntax
#creation of "new" data-frame
lalonde1=lalonde
lalonde1$w=c(rep(0,100),rep(1,214),rep(2,300))
obj <- zelig(treat~black+married, model = "poisson",  robust=list(method="weave"), weights="w",data = mi(lalonde,lalonde1))
summary(obj)

[whatever]

this is mostly an issue with not using "as.name" in the zelig2 method

[jbp1]

the method robust=list(method="weave") yields unlikely small std errors in some cases with lalonde data. So using the default robust = T maybe better: although it does not solve the problem, it avoids adding difficulties.