The asymptotic moment profile and maximum likelihood: Applications to gamma and gamma ratio densities

Abstract

In previous papers ( Bowman and Shenton, 1998, 1999a ) we have given expressions for the asymptotic skewness and kurtosis for maximum likelihood estimators in the case of several parameters. Skewness is measured by the third standardized central moment, and kurtosis by the fourth standardized central moment. Moments of the basic structure are assumed to exist. The overarching entity is the covariance matrix ( Hessian form ), and elements of its inverse. These entities involve Stieltjes integrals relating to sums of products of multiple derivatives linked to the basic structure. The first paper dealt with skewness and gives a simple expression read¬ily computerized. The second paper is devoted to the forth standardized central moment and although a certain simplification is discovered, the resulting formula is still somewhat complicated, ft is surprising to find that the asymptotic kurtosis in general requires the evaluation of several hundred components. The present paper studies cases involving estimator for two parameter gamma and one, and three pa¬rameter gamma ratio densities, and mentions strategies aimed at avoiding algebraic and numerical errors.

Keywords:

• covariance matrix
• gamma density
• generating functions
• products of random variables
• Stieltjes integrals