Copulas are used to specify dependence between two or more random variables. The last
few years have seen a surge of developments of parametric models for copulas. Here, we …

Multiple mechanisms collaborate for proper regulation of gene expression. One layer of this
regulation is through the clustering of functionally related genes at discrete loci throughout …

To study hydrological events, such as floods and droughts, frequency analysis (FA)
techniques are commonly employed. FA relies on some assumptions, especially, the …

The directional dependence between variables using asymmetric copula regression has
drawn much attention in recent years. There are, however, some critical issues which have …

We propose a bivariate Farlie–Gumbel–Morgenstern (FGM) copula model for bivariate meta-
analysis, and develop a maximum likelihood estimator for the common mean vector. With …

This article proposes a new directional dependence by using the Gaussian copula beta
regression model. In particular, we consider an asymmetric Generalized AutoRegressive …

Featured Application This work can be applied to the research and development planning or
sustainable technology management. Abstract The technological keywords extracted from …

ABSTRACT The Conway-Maxwell-Poisson (COM-Poisson) distribution is useful to account
for a cure proportion in survival data. With this model, two computational approaches for …

Linear-dependent variables are typically modeled through the Spearman correlation, a
classical statistical technique. In reality, the dependence between the data cannot always be …

Copula model is introduced in modeling the co-dependence structures of anthropometric
variables-Body mass index (BMI), Abdominal circumference, Adiposity and Percent body fat …