Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Inference for copula modeling of discrete data: a cautionary tale and some facts

Inference for copula modeling of discrete data: a cautionary tale and some facts AbstractIn 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Dependence Modeling de Gruyter

Inference for copula modeling of discrete data: a cautionary tale and some facts

Dependence Modeling , Volume 5 (1): 12 – Jan 26, 2017

Loading next page...
 
/lp/de-gruyter/inference-for-copula-modeling-of-discrete-data-a-cautionary-tale-and-3kzQTlsRfQ
Publisher
de Gruyter
Copyright
© 2017
ISSN
2300-2298
eISSN
2300-2298
DOI
10.1515/demo-2017-0008
Publisher site
See Article on Publisher Site

Abstract

AbstractIn 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.

Journal

Dependence Modelingde Gruyter

Published: Jan 26, 2017

References