We introduce the family of univariate double two–piece distributions, obtained by using a density– based transformation of unimodal symmetric continuous distributions with a shape parameter. The resulting distributions contain five interpretable parameters that control the mode, as well as...

We introduce the family of univariate double two–piece distributions, obtained by using a density– based transformation of unimodal symmetric continuous distributions with a shape parameter. The resulting distributions contain five interpretable parameters that control the mode, as well as...

Frequentist and likelihood methods of inference based on the multivariate skew-normal model encounter several technical difficulties with this model. In spite of the popularity of this class of densities, there are no broadly satisfactory solutions for estimation and testing problems. A general...

Gaussian time-series models are often specified through their spectral density. Such models pose several computational challenges, in particular because of the non-sparse nature of the covariance matrix. We derive a fast approximation of the likelihood for such models. We use importance sampling...

A stationary Gaussian process is said to be long-range dependent (resp., anti-persistent) if its spectral density f(λ) can be written as f(λ)=|λ|−2dg(|λ|), where 0d1/2 (resp., −1/2d0), and g is continuous and positive. We propose a novel Bayesian nonparametric approach for the estimation...

We explore the potential dependence among different Asian stock markets, using several different statistical models. Extreme return-volume dependence in Hong Kong Seng Index, Bombay Stock Exchange, Indonesia Composite Index and Bursa Malaysia has been examined by using FIGARCH-Copula and...

This paper provides a unified treatment and a Bayesian interpretation of two different classes of multivariate skew-normal distributions proposed by Azzalini and Dalla Valle (Biometrika 83 (1996) 715) and Gupta et al. (Tech. Rep., Cimat, Mexico (2001)). We show that the above classes of...