Thinning-based models in the analysis of integer-valued time series: a review

This article aims at providing a comprehensive survey of recent developments in the field of integer-valued time series modelling, paying particular attention to models obtained as discrete counterparts of conventional autoregressive moving average and bilinear models, and based on the concept of th...

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Bibliographic Details
Published inStatistical modelling Vol. 15; no. 6; pp. 590 - 618
Main Authors Scotto, Manuel G., Weiß, Christian H., Gouveia, Sónia
Format Journal Article
LanguageEnglish
Published New Delhi, India SAGE Publications 01.12.2015
Subjects
thinning operators
time series
autocorrelation function(ACF)
counts
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Summary:This article aims at providing a comprehensive survey of recent developments in the field of integer-valued time series modelling, paying particular attention to models obtained as discrete counterparts of conventional autoregressive moving average and bilinear models, and based on the concept of thinning. Such models have proven to be useful in the analysis of many real-world applications ranging from economy and finance to medicine. We review the literature of the most relevant thinning operators proposed in the analysis of univariate and multivariate integer-valued time series with either finite or infinite support. Finally, we also outline and discuss possible directions of future research.
ISSN:1471-082X
1477-0342
DOI:10.1177/1471082X15584701