Inferential Issues on CUBE Models with Covariates

Domenico Piccolo

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 23, 5023-5036

Abstract: We introduce cube models with covariates, a class of discrete mixture distributions able to take uncertainty and overdispersion of ordinal data into account. The main result of the paper concerns the analytical derivation of the observed variance–covariance matrix of this model, a necessary step for the asymptotic inference about estimated parameters and model validation. We emphasize some computational aspects of the procedure and discuss the usefulness of the approach on a real case study.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2013.821487 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:44:y:2015:i:23:p:5023-5036

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2013.821487

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().