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Poisson QMLE of Count Time Series Models
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Document type :
Article dans une revue scientifique
DOI :
10.1111/jtsa.12167
Title :
Poisson QMLE of Count Time Series Models
Author(s) :
Ahmad, Ali [Auteur]
Lille économie management - UMR 9221 [LEM]
Francq, Christian [Auteur]
Laboratoire de Finance Assurance [LFA]
Journal title :
Journal of Time Series Analysis
Pages :
291--314
Publisher :
Wiley-Blackwell
Publication date :
2015-11
ISSN :
0143-9782
English keyword(s) :
Boundary of the parameter space
consistency and asymptotic normality
integer-valued AR and GARCH models
non-normal asymptotic distribution
Poisson quasi-maximum likelihood estimator
time series of counts
HAL domain(s) :
Sciences de l'Homme et Société/Economies et finances
English abstract : [en]
Regularity conditions are given for the consistency of the Poisson quasi-maximum likelihood estimator of the conditional mean parameter of a count time series model. The asymptotic distribution of the estimator is studied ...
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Regularity conditions are given for the consistency of the Poisson quasi-maximum likelihood estimator of the conditional mean parameter of a count time series model. The asymptotic distribution of the estimator is studied when the parameter belongs to the interior of the parameter space and when it lies at the boundary. Tests for the significance of the parameters and for constant conditional mean are deduced. Applications to specific integer-valued autoregressive (INAR) and integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models are considered. Numerical illustrations, Monte Carlo simulations and real data series are provided.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Lille Économie Management (LEM) - UMR 9221
Source :
Harvested from HAL
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  • https://mpra.ub.uni-muenchen.de/59804/1/MPRA_paper_59804.pdf
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