New methods in estimation reveal challenges in finding maximum likelihood.
The article discusses two methods for estimating maximum likelihood when the likelihood function is not smooth. It points out that the solution to the likelihood function may not always be the maximum likelihood estimate, and that there may be cases where the maximum likelihood estimate is not unique or does not exist.
