Detecting overdispersion in INARCH(1) processes

A statistical test for the degree of overdispersion of count data time series based on the empirical version of the (Poisson) index of dispersion is considered. The test design relies on asymptotic properties of this index of dispersion, which in turn have been analyzed for time series stemming from...

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Bibliographic Details
Main Authors: Weiß, Christian (Author) , Schweer, Sebastian (Author)
Format: Article (Journal)
Language:English
Published: 17 February 2015
In: Statistica Neerlandica
Year: 2015, Volume: 69, Issue: 3, Pages: 281-297
ISSN:1467-9574
DOI:10.1111/stan.12059
Online Access:Verlag, Volltext: http://dx.doi.org/10.1111/stan.12059
Verlag, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1111/stan.12059
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Author Notes:Christian H. Weiß, Sebastian Schweer
Description
Summary:A statistical test for the degree of overdispersion of count data time series based on the empirical version of the (Poisson) index of dispersion is considered. The test design relies on asymptotic properties of this index of dispersion, which in turn have been analyzed for time series stemming from a compound Poisson (Poisson-stopped sum) INAR(1) model. This approach is extended to the popular Poisson INARCH(1) model, which exhibits unconditional overdispersion but has an (equidispersed) conditional Poisson distribution. The asymptotic distribution of the index of dispersion if applied to time series stemming from such a model is derived. These results allow us to investigate the ability of the dispersion test to discriminate between Poisson INAR(1) and INARCH(1) models. Furthermore, the question is considered if the index of dispersion could be used to test the null of a Poisson INARCH(1) model against the alternative of an INARCH(1) model with additional conditional overdispersion.
Item Description:Gesehen am 01.06.2018
Physical Description:Online Resource
ISSN:1467-9574
DOI:10.1111/stan.12059