Add to ORKGAbstract. The Poisson model is a benchmark model for the statistical analysis of the count data. Sometimes count data exhibit variation, refered to as overdispersion or un-derdispersion, resulting in the lack of fit of the Poisson model. The aim of this paper is to present an overview of potential families of discrete probability distributions that can provide alternative modelling framework for the statistical analysis of count data
Abstract. We investigate two sets of overdispersed models when Poisson distribution does not fit to ...
Poisson distribution is widely used to model count data, however it has the disadvantage the assump...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...
A variety of methods of modelling overdispersed count data are compared. The methods are classified ...
This article describes the R package CountsEPPM and its use in determining maximum likelihood estima...
For counts it often occurs that the observed variance exceeds the nominal variance of the claimed bi...
We frequently encounter outcomes of count that have extra variation. This paper considers several al...
We present a novel distribution for modelling count data that are underdispersed relative to the Poi...
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...
A popular distribution for the modelling of discrete count data is the Poisson distribution. Howeve...
O modelo de referência para dados de contagem é o modelo de Poisson. A principal característica do m...
En aquest article investiguem dues classes de models exponencials de dispersi¿o (EDMs) per a dades d...
In modeling count data collected from manufacturing processes, eco-nomic series, disease outbreaks a...
Background: The number of counts (events) per unit of time is a discrete response variable that is g...
Abstract. We investigate two sets of overdispersed models when Poisson distribution does not fit to ...
Poisson distribution is widely used to model count data, however it has the disadvantage the assump...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...
A variety of methods of modelling overdispersed count data are compared. The methods are classified ...
This article describes the R package CountsEPPM and its use in determining maximum likelihood estima...
For counts it often occurs that the observed variance exceeds the nominal variance of the claimed bi...
We frequently encounter outcomes of count that have extra variation. This paper considers several al...
We present a novel distribution for modelling count data that are underdispersed relative to the Poi...
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...
A popular distribution for the modelling of discrete count data is the Poisson distribution. Howeve...
O modelo de referência para dados de contagem é o modelo de Poisson. A principal característica do m...
En aquest article investiguem dues classes de models exponencials de dispersi¿o (EDMs) per a dades d...
In modeling count data collected from manufacturing processes, eco-nomic series, disease outbreaks a...
Background: The number of counts (events) per unit of time is a discrete response variable that is g...
Abstract. We investigate two sets of overdispersed models when Poisson distribution does not fit to ...
Poisson distribution is widely used to model count data, however it has the disadvantage the assump...
Repeated count data showing overdispersion are commonly analysed by using a Poisson model with varyi...