The Azzalini Skew-t Information Matrix Evaluation and Use for Standard Error Calculations

49 Pages Posted: 5 Oct 2018

Date Written: September 30, 2018

Abstract

The Azzalini skew-t distributions are popular because of their theoretical foundation and the availability of computational methods in the R package sn. One difficulty with this skew-t family is that the elements of the expected information matrix do not have closed form analytic formulas. Thus, we developed a numerical integration method of computing the expected information matrix in the R package skewtInfo. The accuracy of our expected information matrix calculation method was confirmed by comparing the result with that obtained using an observed information matrix for a very large sample size. A Monte Carlo study to evaluate the accuracy of the finite-sample standard errors obtained with our expected information matrix calculation method, for the case of three realistic skew-t parameter vectors, indicates that use of the expected information matrix results in standard errors as accurate as, and sometimes a little more accurate than, use of an observed information matrix.

Keywords: skew-t distribution, expected information matrix, maximum penalized likelihood estimate, MPLE standard errors

JEL Classification: C13, C40, C46

Suggested Citation

Uthaisaad, Chindhanai and Martin, R. Douglas, The Azzalini Skew-t Information Matrix Evaluation and Use for Standard Error Calculations (September 30, 2018). Available at SSRN: https://ssrn.com/abstract=3258025 or http://dx.doi.org/10.2139/ssrn.3258025

Chindhanai Uthaisaad

WorldQuant ( email )

1700 East Putnam Ave, Third Floor
Old Greenwich, CT 06870
United States

R. Douglas Martin (Contact Author)

University of Washington ( email )

Applied Mathematics & Statistics
Seattle, WA 98195
United States

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