Small sample properties of parameter estimation in the dirichlet distribution

Abstract

A numerically feasible algorithm is proposed for maximum likelihood estimation of the parameters of the Dirichlet distribution. The performance of the proposed method is compared with the method of moments using bias ratio and squared errors by Monte Carlo simulation. For these criteria, it is found that even in small samples maximum likelihood estimation has advantages over the method of moments.

Keywords:

• Multivariate beta distribution
• maximum likelihood
• method of moments
• bias ratio
• squared errors
• Monte Carlo simulation