In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all...

the complex system containing n elements, each having three dependent components are described. the reliability and mean residual life of such systems with intact components at time t are investigated using a trivariate binomial model. considering a farlie-gumbel-morgenstern family, some graphical representations are given.

A new family of distributions called the Kumaraswamy Rayleigh is defied and studied. Some its relevant statistical properties are derived. Many bivariate type G families using Farlie-Gumbel-Morgenstern, modified Farlie-Gumbel-Morgenstern copula, Clayton copula Renyi’s entropy The method maximum likelihood estimation used. special models based on log-logistic, exponential, Weibull, Rayleigh, Par...

A new G family of probability distributions called the type I quasi Lambert is defined and applied for modeling real lifetime data. Some bivariate families using "Farlie-Gumbel-Morgenstern copula", "modified Farlie-Gumbel-Morgenstern "Clayton copula" "Renyi's entropy are derived. Three characterizations presented. its statistical properties derived studied. The maximum likelihood estimation, pr...

Abstract In this paper, a measure of extropy is obtained for concomitants m-generalized order statistics in the Morgenstern family. The cumulative residual (CREX) and negative (NCEX) are presented r th concomitant statistics. addition, problem estimating CREX NCEX studied utilizing empirical method Some applications these results given record values.

Correspondence analysis is a multivariate technique used to visualize categorical data, usually data in a two-way contingency table. Some extensions of correspondence analysis to a continuous bivariate distribution are presented, rstly from a canonical correlation analysis perspective and then from a continuous scaling perspective. These extensions are applied to the Farlie-Gumbel-Morgenstern (...