Testing serial dependence in time series models of counts against some INARMA alternatives

Robert Jung () and Andrew Tremayne

No 204, Tübinger Diskussionsbeiträge from University of Tübingen, School of Business and Economics

Abstract: In analysing time series of counts, the need to test for the presence of a dependence structure routinely arises. Suitable tests for this purpose are considered in this paper.

Keywords: Time series of counts; INARMA models; partial autocorrelation; score test; Monte Carlo (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/47526/1/325461171.pdf (application/pdf)

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:zbw:tuedps:204

Access Statistics for this paper

More papers in Tübinger Diskussionsbeiträge from University of Tübingen, School of Business and Economics Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().