Abstract In this article we present tmvtnorm, an R package implementation for the truncated multivariate normal distribution. We consider random number generation with rejection and Gibbs sampling, computation of marginal densities as well as computation of the mean and covariance of the truncated variables. This contribution brings together latest research in this field and provides useful met...

Abstract The multivariate normal and the multivariate t distributions belong to the most widely used multivariate distributions in statistics, quantitative risk management, and insurance. In contrast to the multivariate normal distribution, the parameterization of the multivariate t distribution does not correspond to its moments. This, paired with a non-standard implementation in the R package...

In this paper we study the multivariate skew-normal distribution and its scale mixtures, as extensions of the similar non-skewed distributions. Different parameterizations and some properties are investigated. ∗ Subject Classification: 60E05.

In this talk, the class of multivariate extended skew normal distributions is introduced. The properties of this class of distributions, such as, the moment generating function, probability density function, conditional probability density functions and independence are discussed. The definition of extended noncentral skew chi-square distribution is given. The necessary and sufficient condition...

In this article, we derive the distribution of partially exchangeable binary random variables, generalizing the distribution of exchangeable binary random variables and hence the binomial distribution. The distribution can also be viewed as a mixture of Markov chains. We introduce rectangular complete monotonicity and show that partial exchangebility can be characterized by rectangular complete...

The need to simulate from a positive multivariate normal distribution arises in several settings, specifically in Bayesian analysis. A variety of algorithms can be used to sample from this distribution, but most of these algorithms involve Gibbs sampling. Since the sample is generated from a Markov chain, the user has to account for the fact that sequential draws in the sample depend on one ano...

The pitch dependency of timbres has not been fully exploited in musical instrument identification. In this paper, we present a method using an F0-dependent multivariate normal distribution of which mean is represented by a function of fundamental frequency (F0). This F0-dependent mean function represents the pitch dependency of each feature, while the F0-normalized covariance represents the non...

Two models for jointly analysing the spatial variation of incidences of three (or more) diseases, with common and uncommon risk factors, are compared via a simulation experiment. In both models, the linear predictor can be decomposed into shared and disease-specific spatial variability components (named shared clustering and specific clustering respectively). The two models are the shared model...