Design of Experiments with Copulas
A direct approach to optimal designs for copula models based on the Fisher information. Provides flexible functions for building joint PDFs, evaluating the Fisher information and finding optimal designs. It includes an extensible solution to summation and integration called 'nint', functions for transforming, plotting and comparing designs, as well as a set of tools for common low-level tasks.
This package builds upon the theoretical result on optimal designs for copula models developed by Elisa Perrone and Werner G. Müller. In their paper named 'Optimal designs for copula models' they introduce an equivalence theorem of Kiefer-Wolfowitz type for D-optimality along with examples and the proof. The proof for D_A-optimality is analogous and is mentioned in an upcoming paper currently under double blind review.
E. Perrone & W.G. Müller (2016) Optimal designs for copula models, Statistics, 50:4, 917-929, DOI: 10.1080/02331888.2015.1111892
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