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A hyper-Poisson regression model for overdispersed and underdispersed count data
Sáez-Castillo, A.J.; Conde-Sánchez, A. - In: Computational Statistics & Data Analysis 61 (2013) C, pp. 148-157
present overdispersion and underdispersion in different levels of the observations. Two applications illustrate that the model …
Persistent link: https://www.econbiz.de/10011056508
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A Poisson mixed model with nonnormal random effect distribution
Fabio, Lizandra C.; Paula, Gilberto A.; Castro, Mário de - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 1499-1510
generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and …
Persistent link: https://www.econbiz.de/10011056529
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Dirichlet-Multinomial Regression
Guimaraes, Paulo; Lindrooth, Richard - EconWPA - 2005
In this paper we provide a Random-Utility based derivation of the Dirichlet-Multinomial regression and posit it as a convenient alternative for dealing with overdispersed multinomial data. We show that this model is a natural extension of McFadden's conditional logit for grouped data and show...
Persistent link: https://www.econbiz.de/10005119073
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Recreation Demand Analysis under Truncation, Overdispersion, and Endogenous Stratification: An Application to Gros Morne National Park
Martinez-Espineira, Roberto; Amoako-Tuffour, Joe - EconWPA - 2005
specification of the overdispersion parameter dominates on the basis of goodness of fit. The results are used to estimate the users …
Persistent link: https://www.econbiz.de/10005119149
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Parametric frailty and shared frailty survival models
Gutierrez, Roberto G. - In: Stata Journal 2 (2002) 1, pp. 22-44
Frailty models are the survival data analog to regression models, which account for heterogeneity and random effects. A frailty is a latent multiplicative effect on the hazard function and is assumed to have unit mean and variance theta, which is estimated along with the other model parameters....
Persistent link: https://www.econbiz.de/10005568783
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Zero‐modified discrete distributions for operational risk modelling
Mouatassim, Younès - In: The Journal of Risk Finance 13 (2012) 5, pp. 476-490
Purpose – The purpose of this paper is to introduce the zero‐modified distributions in the calculation of operational value‐at‐risk. Design/methodology/approach – This kind of distributions is preferred when excess of zeroes is observed. In operational risk, this phenomenon may be due...
Persistent link: https://www.econbiz.de/10014901620
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Modelling unobserved heterogeneity in claim counts using finite mixture models
Bermúdez, Lluís; Karlis, Dimitris; Morillo, Isabel - In: Risks : open access journal 8 (2020) 1/10, pp. 1-13
When modelling insurance claim count data, the actuary often observes overdispersion and an excess of zeros that may be … caused by unobserved heterogeneity. A common approach to accounting for overdispersion is to consider models with some … models. This approach has interesting features: first, it allows for overdispersion and the zero-inflated model represents a …
Persistent link: https://www.econbiz.de/10012204036