Assessing copula models for mixed continuous-ordinal variables

Pan Shenyi () and Joe Harry ()
Additional contact information
Pan Shenyi: Department of Statistics, University of British Columbia, Vancouver, BC Canada V6T 1Z4, Canada
Joe Harry: Department of Statistics, University of British Columbia, Vancouver, BC Canada V6T 1Z4, Canada

Dependence Modeling, 2024, vol. 12, issue 1, 18

Abstract: Vine pair-copula constructions exist for a mix of continuous and ordinal variables. In some steps, this can involve estimating a bivariate copula for a pair of mixed continuous-ordinal variables. To assess the adequacy of copula fits for such a pair, diagnostic and visualization methods based on normal score plots and conditional Q–Q plots are proposed. The former uses a latent continuous variable for the ordinal variable. The methods are applied to data generated from some existing probability models for a mixed continuous-ordinal variable pair, and for such models, Kullback-Leibler divergence is used to assess whether simple parametric copula families can provide adequate fits. The effectiveness of the proposed visualization and diagnostic methods is illustrated on a dataset.

Keywords: parametric copula; empirical beta copula; Kullback-Leibler divergence; location-scale mixture models; normal scores; ordinal regression; polyserial correlation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/demo-2024-0001 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:12:y:2024:i:1:p:18:n:1001

DOI: 10.1515/demo-2024-0001

Access Statistics for this article

Dependence Modeling is currently edited by Giovanni Puccetti

More articles in Dependence Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().