In this paper we investigate two classes of exponential dispersion models (EDMs) for overdispersed count data with respect to the Poisson distribution. The first is a class of Poisson mixture with positive Tweedie mixing distributions. As an approximation (in terms of unit variance function) of the first, the second is a new class of EDMs characterized by their unit variance functions of the form µ+ µp, where p is a real index related to a precise model. These two classes provide some alternatives to the negative binomial distribution (p = 2) which is classically used in the framework of regression models for count data when overdispersion results in a lack of fit of the Poisson regression model. Some properties are then studied and the pra...
The Poisson regression model remains an important tool in the econometric analysis of count data. In...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...
Regression for count data is widely performed by models such as Poisson, negative binomial (NB) and ...
In this paper we investigate two classes of exponential dispersion models (EDMs) for overdispersed c...
In this paper we investigate two classes of exponential dispersion models (EDMs) for overdispersed c...
Abstract. We investigate two sets of overdispersed models when Poisson distribution does not fit to ...
En aquest article investiguem dues classes de models exponencials de dispersi¿o (EDMs) per a dades d...
We investigate two sets of overdispersed models when Poisson distribution does not fit to count data...
In this paper we introduce the Hinde-Demétrio (HD) regression models for ana-lyzing overdispersed co...
We propose a new class of discrete generalized linear models based on the class of Poisson-Tweedie f...
In their fundamental paper on cubic variance functions (VFs), Letac and Mora (The Annals of Statisti...
In their fundamental paper on cubic variance functions (VFs), Letac and Mora (The Annals of Statisti...
This article describes the R package CountsEPPM and its use in determining maximum likelihood estima...
A variety of methods of modelling overdispersed count data are compared. The methods are classified ...
A popular distribution for the modelling of discrete count data is the Poisson distribution. Howeve...
The Poisson regression model remains an important tool in the econometric analysis of count data. In...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...
Regression for count data is widely performed by models such as Poisson, negative binomial (NB) and ...
In this paper we investigate two classes of exponential dispersion models (EDMs) for overdispersed c...
In this paper we investigate two classes of exponential dispersion models (EDMs) for overdispersed c...
Abstract. We investigate two sets of overdispersed models when Poisson distribution does not fit to ...
En aquest article investiguem dues classes de models exponencials de dispersi¿o (EDMs) per a dades d...
We investigate two sets of overdispersed models when Poisson distribution does not fit to count data...
In this paper we introduce the Hinde-Demétrio (HD) regression models for ana-lyzing overdispersed co...
We propose a new class of discrete generalized linear models based on the class of Poisson-Tweedie f...
In their fundamental paper on cubic variance functions (VFs), Letac and Mora (The Annals of Statisti...
In their fundamental paper on cubic variance functions (VFs), Letac and Mora (The Annals of Statisti...
This article describes the R package CountsEPPM and its use in determining maximum likelihood estima...
A variety of methods of modelling overdispersed count data are compared. The methods are classified ...
A popular distribution for the modelling of discrete count data is the Poisson distribution. Howeve...
The Poisson regression model remains an important tool in the econometric analysis of count data. In...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...
Regression for count data is widely performed by models such as Poisson, negative binomial (NB) and ...