Aligned signed-rank tests of a linear autoregressive model against an exponential autoregressive one

Allal Jelloul, Nabil Azouagh and Said El Melhaoui

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 22, 7944-7965

Abstract: In this work, we have established the aligned signed-rank tests for testing the ordinary AR(1) dependence against exponential autoregression [EXPAR(1)] model. The considered tests are asymptotically valid under an arbitrary symmetric innovation density, and locally asymptotically most stringent against the EXPAR alternatives associated with some predetermined symmetric density type. Several simulation was curried out to show the good performance of these tests and an application for modeling the annual sunspots number is provided.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2052898 (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:52:y:2023:i:22:p:7944-7965

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

DOI: 10.1080/03610926.2022.2052898

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 ().