Estimating density functions: A constrained maximum likelihood approach

We propose estimating density functions by means of a constrained optimizat ion problem whose criterion function is the maximum likelihood function, an d whose constraints model any (prior) information that might be available. The asymptotic justification for such an approach relies on the theory of e pi-convergence. A simple numerical example is used to signal the potential of such an approach.