The Azzalini Skew-t Information Matrix Evaluation and Use for Standard Error Calculations
49 Pages Posted: 5 Oct 2018
Date Written: September 30, 2018
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
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