Multivariate Logistic Distributions

Information Covariance Matrices for Multivariate Burr III and Logistic Distributions

Main result of this paper is to derive the exact analytical expressions of information and covariance matrices for multivariate Burr III and logistic distributions. These distributions arise as tractable parametric models in price and income distributions, reliability, economics, Human population, some biological organisms to model agricultural population data and survival data. We showed that ...

Bayesian multivariate logistic regression.

Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual outcomes. In addition, difficulties arise when simple noninformative priors are chosen for the covariance parameters. Motivated by these problems, we propose a new type of multivariate logistic dis...

Tutorial on Multivariate Logistic Regression

Concentration Inequalities for Multivariate Distributions: I. Multivariate Norivial Distributions

Let X rv Np(O, E), the p-variate normal distribution with mean °and positive definite covariance matrix .E. Anderson (1955) showed that if .E2 .E1 is positive semidefinite then PEl (C) 2: P E2(C) for every centrally symmetric (-C = convex set C ~ RP. Fefferman, Jodeit, and Perlman (1972) extended this result to elliptically contoured distributions. In the present paper similar multivariate f f"...

Multivariate matrix-exponential distributions

In this extended abstract we define a class of distributions which we shall refer to as multivariate matrix–exponential distributions (MVME). They are defined in a natural way, inspired by the definition of univariate matrix– exponential distributions, as the distributions on R+ having a rational (multidimensional) Laplace transform. A multidimensional rational function is the fraction between ...