On the maximum likelihood estimation of a discrete, finite support distribution under left-truncation and competing risks

We prove the classical cause-specific hazard rate estimator is a maximum likelihood estimate (MLE) in a discrete-time, finite support setting. We use an alternative parameterization to simplify the multidimensional constrained optimization problem, which allows for a direct calculus-based solution.