Hi,

When I run the following code :

Y <- c(rep(0,35),1,2,0,6,8,16,43)
cst <- log(choose(42, 42:1)) 
beta <- 42:1
tau <- (beta^2)/2
fit <- glm(formula = Y ~ offset(cst) + beta + tau, family = poisson)
fit
fit$converged

glm prints a warning saying that the algorithm did not converge.
However, fit$converged takes the value TRUE.

I don't understand why fit$converged is not always FALSE when the warning 
"algorithm did not converge" is produced. Could someone help me understand why 
I get this result?

Thanks a lot,
 
Sophie

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