This research work investigates the theoretical foundations and computational aspects of constructing optimal bespoke CDO structures. Due to the evolutionary nature of the CDO design process, stochastic search methods that mimic the metaphor of natural biological evolution are applied. For efficient searching the optimal solution, the nondominating sort genetic algorithm NSGA-II is used, which ...

A new generalization of Burr type XII model is introduced and studied. The genesis the based on family Cordeiro et al. (2016). generalizes at least eight important sub-models. density can be unimodal, symmetric left skewed. Some useful properties related to are derived. Clayton Copula-based construction used generate many bivariate multivariate distributions. Graphically, we performed simulatio...

In life history studies, interest often lies in the analysis of the interevent, or gap times and the association between event times. Gap time analyses are challenging however, even when the length of follow-up is determined independently of the event process, because associations between gap times induce dependent censoring for second and subsequent gap times. This article discusses nonparamet...

This paper follows Jones (2005) in his approach to deriving the global production function from microfoundations. His framework is generalized by allowing for dependence between the Pareto distributions of laborand capital-augmenting developments. Using the Clayton copula family to capture this dependence, we derive a “Clayton-Pareto” class of production functions that nests both the Cobb-Dougl...

This paper follows Jones (2005) in his approach to deriving the global production function from microfoundations. His framework is generalized by allowing for dependence between the Pareto distributions of laborand capital-augmenting developments. Using the Clayton copula family to capture this dependence, we derive a “Clayton-Pareto” class of production functions that nests both the Cobb-Dougl...

In the standard stochastic frontier model, the two-sided error term V and the one-sided technical inefficiency error term W are assumed to be independent. In this paper, we relax this assumption by modeling the dependence between V and W using copulas. Nine copula families are considered and their parameters are estimated using maximum simulated likelihood. The best model is then selected using...

We provide the learning of a DAG model arising from high dimensional random variables following both normal and non-normal assumptions. To this end, copula function utilized connecting dependent variables. Moreover to copula, three most applicable copulas have been investigated modeling all dependence structures negative, positive, weak kinds. The functions, FGM, Clayton, Gumbel are considered ...

Parametric conditional copula models allow the copula parameters to vary with a set of covariates according to an unknown calibration function. In this paper we develop a flexible Bayesian method to estimate the calibration function of a bivariate conditional copula. We construct a prior distribution over the set of smooth calibration functions using a sparse Gaussian process (GP) prior for the...