The likelihood equation for a logistic regression model does not always have a finite solution. Sometimes there is a nonunique maximum on the boundary of the parameter space, at infinity. The ...

The authors consider the empirical likelihood method for the regression model of mean qualityadjusted lifetime with right censoring. They show that an empirical log-likelihood ratio for the vector of ...

Bayesian inference provides a flexible way of combining data with prior information. However, quantile regression is not equipped with a parametric likelihood, and therefore, Bayesian inference for ...

Abstract: In this paper, we present an expectation maximization (EM) based simultaneous registration and fusion algorithm for multiple radars network. This simultaneous registration and fusion ...

Abstract: The selection of classifiers which are profitable is becoming more and more important in real-life situations such as customer churn management campaigns in the telecommunication sector. In ...