Significance Test for Sphericity of a Normal $n$-Variate Distribution

On Conditional Applications of Matrix Variate Normal Distribution

In this paper, by conditioning on the matrix variate normal distribution (MVND) the construction of the matrix t-type family is considered, thus providing a new perspective of this family. Some important statistical characteristics are given. The presented t-type family is an extension to the work of Dickey [8]. A Bayes estimator for the column covariance matrix &Sigma of MVND is derived under ...

Matrix Variate ^-generalized Normal Distribution

In this paper, the matrix variate ^-generalized normal distribution is introduced. Then its properties are studied. In particular, it is proved that this distribution has maximal entropy in a certain class of distributions.

A Note on Matrix Variate Normal Distribution

Let X1 and X2 be two identically distributed random variables. Suppose that X1 | X2=x2 has a N(ax2+b, _) distribution for all x2 # R, where & 0. Ahsanullah (1985) showed that these conditions imply |a|<1, X1 , and X2 have a common normal distribution with mean b (1&a;) and variance _ (1&a;), and the joint distribution of X1 and X2 is a bivariate normal distribution with covariance a_ (...

A New Approximation for the Null Distribution of the Likelihood Ratio Test Statistics for k Outliers in a Normal Sample

Usually when performing a statistical test or estimation procedure, we assume the data are all observations of i.i.d. random variables, often from a normal distribution. Sometimes, however, we notice in a sample one or more observations that stand out from the crowd. These observation(s) are commonly called outlier(s). Outlier tests are more formal procedures which have been developed for detec...

Screening for a Multivariate Mixture Normal Distribution