Abstract
Copula functions also known as copulas, which connect the marginal distributions to their joint distributions, are useful in simulating the linear or nonlinear relationships among multivariate data in the scientific and engineering studies. Copula is a multivariate distribution function with marginally uniform random variables on [0, 1]. Copula functions have some appealing properties such as they allow scale-free measures of dependence and are useful in constructing families of joint distributions. As seen recently, copulas have been applied in statistics, insurance, finance, economics, survival analysis, image processing, and engineering applications. In this paper, we aim to briefly describe the copula functions, their properties, copula families, simulations, and examples of copula applications.
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