Unusual-event processes for count data
Skulpakdee, Wanrudee (Graduate School of Applied Statistics, National Institute of Development Administration (Tailàndia))
Hunkrajok, Mongkol (Tailàndia)

Date:	2022
Abstract:	At least one unusual event appears in some count datasets. It will lead to a more concentrated (or dispersed) distribution than the Poisson, gamma, Weibull, Conway-Maxwell-Poisson (CMP), and Faddy (1997) models can accommodate. These well-known count models are based on the monotonic rates of interarrival times between successive events. Under the assumption of non-monotonic rates and independent exponential interarrival times, a new class of parametric models for unusual-event (UE) count data is proposed. These models are applied to two empirical applications, the number of births and the number of bids, and yield considerably better results to the above well-known count models.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Poisson count model ; Gamma count model ; Weibull count model ; Conway-Maxwell-Poisson count model ; Faddy count model
Published in:	SORT : statistics and operations research transactions, Vol. 46 Núm. 1 (2022) , p. 39-66 (Articles) , ISSN 2013-8830

Adreça original: https://raco.cat/index.php/SORT/article/view/401117
DOI: 10.2436/20.8080.02.117

28 p, 1.2 MB

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