Optimal designs for copula models. Issue 4 (3rd July 2016)

• Record Type: Journal Article
• Authors: Perrone, E.; Müller, W.G.
• Is Part Of: Statistics. Volume 50:Issue 4(2016)
• Page Start: 917
• Page End: 929
• Publication Date: 2016-07-03
• Subjects: copulas -- design measure -- Fisher information -- stochastic dependence -- clinical trials; 62K05; Mathematical statistics -- Periodicals; 519.505
• DOI: 10.1080/02331888.2015.1111892
• Languages: English
• ISSNs: 0233-1888

Abstract

Abstract : Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well.