On Mixture, Quasi-mixture and Nearly Normal Random Processes

Screening for a Multivariate Mixture Normal Distribution

Finite Mixture Distributions with Skew Normal Components

This article has no abstract.

Poisson processes (and mixture distributions)

MiDGaP: Mixture Density Gaussian Processes

Gaussian Processes (GPs) have become a core technique in machine learning over the last decade, with numerous extensions and applications. Although several approaches exist for warping the conditional Gaussian posterior distribution to other members of the exponential family, most tacitly assume a unimodal posterior. In this paper we present a mixture density model (MDM) allowing multi-modal po...

Asymmetric multivariate normal mixture GARCH

An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic correlation structure of the process are provided. In an application to stock market returns, it is ...