In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.
@article{bwmeta1.element.doi-10_1515_demo-2017-0008,
author = {Olivier P. Faugeras},
title = {Inference for copula modeling of discrete data: a cautionary tale and some facts},
journal = {Dependence Modeling},
volume = {5},
year = {2017},
pages = {121-132},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.doi-10_1515_demo-2017-0008}
}
Olivier P. Faugeras. Inference for copula modeling of discrete data: a cautionary tale and some facts. Dependence Modeling, Tome 5 (2017) pp. 121-132. http://gdmltest.u-ga.fr/item/bwmeta1.element.doi-10_1515_demo-2017-0008/