On multiple constraint skewed models

Abstract

The Azzalini [A. Azzalini, A class of distributions which includes the normal ones, Scandi. J. Statist. 12 (1985), pp. 171–178.] skew normal model can be viewed as one involving normal components subject to a single linear constraint. As a natural extension of this model, we discuss skewed models involving multiple linear and nonlinear constraints and possibly non-normal components. Particular attention is devoted to a distribution called the extended two-piece normal (ETN) distribution. This model is a two-constraint extension of the two-piece normal model introduced by Kim [H.J. Kim, On a class of two-piece skew normal distributions, Statistics 39(6) (2005), pp. 537–553.]. Likelihood inference for the ETN distribution is developed and illustrated using two data sets.

Keywords:

• two-piece skew normal
• multiple constraints
• skew normal
• maximum likelihood
• information matrix

Acknowledgements

HW Gómez was partially supported by grant FONDECYT 1060727|7070074 while HS Salinas was partially supported by DIUDA-221153.