Before revision:  We show that some, but not all, GLMs can still deliver consistent , uniquely-identified maximum likelihood estimates of at least some of the linear parameters at the boundary of the parameter space when these conditions fail to hold.
After revision:  We show that some, but not all, GLMs can still deliver consistent estimates of at least some of the linear parameters at the boundary of the parameter space when these conditions fail to hold.