Maximum Likelihood Infinite Mixture Distribution Estimation Utilizing Finite Gaussian Mixtures^⁎

In this paper we develop a Maximum Likelihood estimation algorithm for the estimation of infinite mixture distributions. We assume a known conditional distribution, whilst the weighting distribution is assumed unknown and it is approximated by a finite Gaussian mixture. Our approach allows for the correct estimation of the Gaussian mixture parameters. We illustrate the estimation performance of our proposal with numerical simulations.