Copulae is a growing field of interest and application for dependency modelling. There is however no predominant way of choosing the copula model that best fits a given data set. We introduce a new goodness-of-fit test, based on the probability integral transform. The test is consistent, numerically efficient and incorporates a weighting functionality. Results show that the test performs well a...

The contribution of this paper is twofold. First, we exploit copula methodology, with two threshold GARCH models as marginals, to construct a bivariate copula-threshold-GARCH model, simultaneously capturing asymmetric nonlinear behaviour in univariate stock returns of spot and futures markets and bivariate dependency, in a flexible manner. Two elliptical copulas (Gaussian and Student’s-t) and t...

A new two-parameter lifetime distribution is proposed and numerically studied. The model has a flflexible failure rate shapes such as “monotonically increasing” , decreasing” “bathtub” “constant” “upside down” “J-shape” . Various of its statistical properties are derived. numerical analysis skewness kurtosis presented. Many bivariate multivariate extensions also presented via Farlie Gumbel Morg...

Tail dependence copulas provide a natural perspective from which one can study the dependence in the tail of a multivariate distribution. For Archimedean copulas with continuously differentiable generators, regular variation of the generator near the origin is known to be closely connected to convergence of the corresponding lower tail dependence copulas to the Clayton copula. In this paper, th...

Abstract In this article, a new reciprocal Rayleigh extension called the Xgamma model is defined and studied. The relevant statistical properties are derived, useful results related to convexity concavity addressed. We discussed estimation of parameters using different methods such as maximum likelihood method, ordinary least squares weighted Cramer-Von-Mises bootstrapping method. A simulation ...

Parametric conditional copulamodels allow the copula parameters to vary with a set of covariates according to an unknown calibration function. Flexible Bayesian inference for the calibration function of a bivariate conditional copula is introduced. The prior distribution over the set of smooth calibration functions is built using a sparse Gaussian process (GP) prior for the single index model (...

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...

Probability distributions and their families play an effective role in statistical modeling analysis. Recently, researchers have been increasingly interested generating new with high flexibility low number of milestones. We propose study a family continuous distributions. Relevant properties are presented. Many bivariate versions the derived under Farlie-Gumbel-Morgenstern copula, modified Clay...