‎Here we consider  a new class of skew logistic  distribution as a generalized mixture of the standard logistic and skew logistic distributions‎, ‎and study some of its important aspects‎. ‎The tail behaviour of the  distribution is compared with that of the skew logistic distribution and a location-scale extension of the distribution is proposed‎. ‎Fu...

This work develops diagnostics for skew-t-normal nonlinear models which provides an useful extension for ordinary normal regression models when the data set under consideration involves heavy tail and asymmetric outcomes. The case-deletion model (CDM) is considered, and several diagnostic measures are derived and discussed. Furthermore, we discuss score test for homogeneity of the variance in s...

A local likelihood estimator for a nonparametric nuisance function is proposed in the context of semiparametric skew-normal distributions. Constraints imposed on such functions result in a nonparametric estimator with a different target function for maximization from classical local likelihood estimators. The optimal asymptotic semiparametric efficiency bound on parameters of interest is achiev...

Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scalemixture class of closed skew-normal distributions. Some basic properties are derived and a class of closed skew-t distributions is obtained. Our suggested family of...

It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace tra...

In recent years, the skew-normal models introduced by Azzalini (1985)—and their multivariate generalizations from Azzalini and Dalla Valle (1996)—have enjoyed an amazing success, although an important literature has reported that they exhibit, in the vicinity of symmetry, singular Fisher information matrices and stationary points in the profile log-likelihood function for skewness, with the usu...