EconPapers    
Economics at your fingertips  
 

Conditional maximum likelihood estimation in negative binomial INGARCH processes with known number of successes when the true parameter is at the boundary of the parameter space

Yunwei Cui and Xiaoyin Wang

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 13, 3388-3401

Abstract: The paper establishes the asymptotic distribution of the conditional maximum likelihood estimator for integer-valued generalized autoregressive conditional heteroskedastic (INGARCH) processes of conditional negative binomial distributions, with the number of successes in the definition of the negative binomial distribution being assumed to be known, when the true parameter is at the boundary of the parameter space. Based on the result, coefficient nullity tests are developed for model simplification. The proposed tests are investigated through a simulation study.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2018.1476710 (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:48:y:2019:i:13:p:3388-3401

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

DOI: 10.1080/03610926.2018.1476710

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 ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:48:y:2019:i:13:p:3388-3401