Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247543 
Authors: 
Year of Publication: 
2019
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 7 [Issue:] 4 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-13
Publisher: 
MDPI, Basel
Abstract: 
For modeling count time series data, one class of models is generalized integer autoregressive of order p based on thinning operators. It is shown how numerical maximum likelihood estimation is possible by inverting the probability generating function of the conditional distribution of an observation given the past p observations. Two data examples are included and show that thinning operators based on compounding can substantially improve the model fit compared with the commonly used binomial thinning operator.
Subjects: 
binomial thinning
compounding operation
count time series
self-generalized property
thinning operators
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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