Copulas enable to specifymultivariate distributions with givenmarginals.Various parametric proposals weremade in the literature for these quantities, mainly in the bivariate case. They can be systematically derived from multivariate distributions with known marginals, yielding e.g. the normal and the Student copulas. Alternatively, one can restrict his/her interest to a sub-family of copulas na...

A new Archimedean copula family is presented that was derived from the SAHARA utility function introduced in economic literature 2011. Its properties are discussed, and its flexibility versatility demonstrated. It left tail decreasing or right increasing, but unlike mainstream families, not necessarily stochastically increasing at same time. shown fits very well to a dataset of previously studi...

We review the main “omnibus procedures” for goodness-of-fit testing for copulas: tests based on the empirical copula process, on probability integral transformations, on Kendall’s dependence function, etc, and some corresponding reductions of dimension techniques. The problems of finding asymptotic distribution-free test statistics and the calculation of reliable p-values are discussed. Some pa...

Rivest & Wells (2001) proposed estimators of the marginal survival functions in a right-censored model that assumes an Archimedean copula between the survival time and the censoring time. We study the extension of these estimators to the context of rightcensored semi-competing risks data with an independent second level censoring time. We intensively use martingale techniques to derive their la...

In this paper, we investigate the problem of linear joint probabilistic constraints. We assume that the rows of the constraint matrix are dependent and the dependence is driven by a convenient Archimedean copula. Further we assume the distribution of the constraint rows to be elliptically distributed, covering normal, t, or Laplace distributions. Under these and some additional conditions, we p...

In this paper we characterize the identified set and construct asymptotically valid and non-conservative confidence sets for the quantile regression coeffi cient in a linear quantile regression model, where the dependent variable is subject to possibly dependent censoring. The underlying censoring mechanism is characterized by an Archimedean copula for the dependent variable and the censoring v...

The copula function is an effective and elegant tool useful for modeling dependence between random variables. Among the many families of this function, one most prominent family Archimedean family, which has its unique structure features. Most functions in have only a single parameter limits scope structure. In paper we modify generator copulas way maintains membership while increasing number p...