Multivariate semi-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...

Semi Supervised Logistic Regression

Semi-supervised learning has recently emerged as a new paradigm in the machine learning community. It aims at exploiting simultaneously labeled and unlabeled data for classification. We introduce here a new semi-supervised algorithm. Its originality is that it relies on a discriminative approach to semisupervised learning rather than a generative approach, as it is usually the case. We present ...

Tutorial on Multivariate Logistic Regression

Bivariate Semi-Logistic Distribution and Processes

Bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions are introduced. Some properties of these distributions are studied. First order autoregressive processes with bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions as marginals are introduced and studied.