The estimation of coe±cients in a simple regression model with autocorrelated errors is considered. The underlying distribution is assumed to be symmetric, one of Student's t family for illustration. Closed form estimators are obtained and shown to be remarkably e±cient and robust. Skew distributions will be considered in a future paper.

In recent years, the skew-normal models introduced in Azzalini (1985) 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 usual unpleasant consequences for inference. For general multivariate skew-symm...

This article introduces a bimodal model based on the epsilon-skew-normal distribution. extension generates distributions similar to those produced by mixture of normal distributions. We study basic properties this new family. apply maximum likelihood estimators, calculate information matrix and present simulation assess parameter recovery. Finally, we illustrate results three real data sets, su...

We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by a common variance. We also introduce the modeling of skew using the Normal Variance-Mean mixture model. We give closed form expressions for likelihoods and parameter updates in the EM algorithm.