By default when we use a
glm function in R, it uses the iteratively reweighted least squares (IWLS) method to find the maximum likelihood estimation the parameters. Now I have two questions.
- Does IWLS estimations guarantee the global maximum of the likelihood function? Based on the last slide in this presentation, I think it does not! I just wanted to make sure of that.
- Can we say that the reason for question 1 above is because of the fact that almost all the numerical optimization methods may stuck at a local maximum rather than a global maximum?