A moment-based test for conditional Poissonity in integer-valued conditional autoregressive models

Junmo Song () and Jiwon Kang ()
Additional contact information
Junmo Song: Kyungpook National University, Department of Statistics
Jiwon Kang: Jeju National University, Department of Data Science

Statistical Papers, 2025, vol. 66, issue 7, No 14, 27 pages

Abstract: Abstract The Poisson distribution, a fundamental tool in the analysis of discrete data, holds a position of importance comparable to that of the normal distribution in continuous data analysis. This distribution has been widely employed in many time series models developed for count data. However, the question of whether the Poisson assumption is valid in these models has received limited attention. This study specifically addresses testing for conditional Poissonity within integer-valued conditional autoregressive models. To this end, we propose a moment-based test statistic and derive its asymptotic null distribution under regularity conditions. We also extend the test to evaluate conditional negative binomiality. Simulation results confirm the validity and effectiveness of the test. Finally, we illustrate its application through a real data analysis.

Keywords: Integer-valued conditional autoregressive models; Poisson autoregressive models; Test for conditional Poissonity; Test for conditional negative binomiality; INGARCH models (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00362-025-01753-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:stpapr:v:66:y:2025:i:7:d:10.1007_s00362-025-01753-3

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-025-01753-3

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().