Nonlinear mixed–effects models are very useful to analyze repeated measures data and are used in a variety of applications. Normal distributions for random effects and residual errors are usually assumed, but such assumptions make inferences vulnerable to the presence of outliers. In this work, we introduce an extension of a normal nonlinear mixed–effects model considering a subclass of ellipti...

A new class of densities for modelling non-negative data, which is based on the skew-symmetric family distributions proposed by Azzalini introduced.We focus model generated skew-normal distribution, called Extended Half Skew-Normal distribution. Its relevant properties are studied. These pdf, cdf, moments, mgf, and stochastic representation. The parameters estimated moment maximum likelihood me...

We study the class of logarithmic skew-normal (LSN) distributions. They have heavy tails; however, all their moments of positive integer orders are finite. We are interested in the problem of moments for such distributions. We show that the LSN distributions are all nonunique (moment-indeterminate). Moreover, we explicitly describe Stieltjes classes for some LSN distributions; they are families...

Mulitvariate stable distributions with elliptical contours are a class of heavy tailed distributions that can be useful for modeling financial data. This paper describes the theory of such distributions, presents formulas for calculating their densities, methods for fitting the data and assessing the fit. Numerical routines are described that work for dimension d ≤ 40. An example looks at a por...