Modeling time series of counts with a new class of INAR(1) model

Wooi Chen Khoo (), Seng Huat Ong () and Atanu Biswas ()
Additional contact information
Wooi Chen Khoo: University of Malaya
Seng Huat Ong: University of Malaya
Atanu Biswas: Indian Statistical Institute

Statistical Papers, 2017, vol. 58, issue 2, No 6, 393-416

Abstract: Abstract This paper presents a new model for a stationary non-negative first order of integer-valued random variables based on the Pegram and thinning operators. Some fundamental and regression properties of the proposed model are discussed. Maximum likelihood estimation (MLE) by the EM algorithm is applied to estimate the parameters. Numerical studies to compare the proposed model with the thinning and Pegram models and the breakdown point of MLE for the proposed model have been conducted. Finally, a real life count data set has been used to illustrate its application. Comparison with existing models by AIC showed that the proposed model is much better and illustrates its potential usefulness in empirical modeling.

Keywords: Pegram operator; Thinning operator; Mixture; EM algorithm; Robustness; Additive and innovative outliers; 60G10; 62M10 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s00362-015-0704-0 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:58:y:2017:i:2:d:10.1007_s00362-015-0704-0

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

DOI: 10.1007/s00362-015-0704-0

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 ().