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|a 10.1080/02664763.2023.2179567
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|a eng
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|a Diop, Mamadou Lamine
|e verfasserin
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|a Epidemic change-point detection in general integer-valued time series
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|c 2024
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|a Text
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|a ƒaComputermedien
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|a Date Revised 25.04.2024
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|a published: Electronic-eCollection
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|a Citation Status PubMed-not-MEDLINE
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|a © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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|a In this paper, we consider the structural change in a class of discrete valued time series, where the true conditional distribution of the observations is assumed to be unknown. The conditional mean of the process depends on a parameter θ∗ which may change over time. We provide sufficient conditions for the consistency and the asymptotic normality of the Poisson quasi-maximum likelihood estimator (QMLE) of the model. We consider an epidemic change-point detection and propose a test statistic based on the QMLE of the parameter. Under the null hypothesis of a constant parameter (no change), the test statistic converges to a distribution obtained from increments of a Browninan bridge. The test statistic diverges to infinity under the epidemic alternative, which establishes that the proposed procedure is consistent in power. The effectiveness of the proposed procedure is illustrated by simulated and real data examples
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|a Journal Article
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|a 62F12
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|a 62M10
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|a Discrete valued time series
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| 650 |
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4 |
|a Poisson QMLE
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| 650 |
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4 |
|a change-point detection
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| 650 |
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|a epidemic alternative
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| 650 |
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|a semi-parametric statistic
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|a Kengne, William
|e verfasserin
|4 aut
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|i Enthalten in
|t Journal of applied statistics
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|g 51(2024), 6 vom: 01., Seite 1131-1150
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|g volume:51
|g year:2024
|g number:6
|g day:01
|g pages:1131-1150
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|u http://dx.doi.org/10.1080/02664763.2023.2179567
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