Results 261 to 270 of about 215,563 (295)

A NEW MIXTURE MODEL FROM GENERALIZED POISSON AND GENERALIZED INVERSE GAUSSIAN DISTRIBUTION

Far East Journal of Theoretical Statistics, 2017
Summary: In this paper, we propose a new distribution for modeling count datasets with some unique characteristics, obtained by mixing the generalized Poisson distribution (GPD) and the generalized inverse Gaussian distribution (GIGD) and using the framework of the Lagrangian probability distribution.
Olumoh, J. S., Sanni, O. O. M., Ajayi, O. O., Jolayemi, E. T.   +3 more
openaire   +1 more source

Estimation of count data using mixed Poisson, generalized Poisson and finite Poisson mixture regression models

AIP Conference Proceedings, 2014
This study relates the Poisson, mixed Poisson (MP), generalized Poisson (GP) and finite Poisson mixture (FPM) regression models through mean-variance relationship, and suggests the application of these models for overdispersed count data. As an illustration, the regression models are fitted to the US skin care count data.
Hossein Zamani, Pouya Faroughi, Noriszura Ismail   +2 more
openaire   +1 more source

Diagnostics analysis in censored generalized Poisson regression model

Journal of Statistical Computation and Simulation, 2007
In this article, we develop the application of influence diagnostics in censored generalized Poisson regression (CGPR) models based on case-deletion method and local influence analysis. The one-step approximations of the estimates in the case-deletion model are given and case-deletion measures, such as generalized Cook distance, likelihood distance are
Feng-Chang Xie, Bo-Cheng Wei
openaire   +1 more source

Functional Form for the Generalized Poisson Regression Model

Communications in Statistics - Theory and Methods, 2012
This article develops a functional form of the generalized Poisson regression model that parametrically nests the Poisson and the two well known generalized Poisson regression models (GP-1 and GP-2). The proposed model is applied on the Malaysian motor insurance claim count data.
Hossein Zamani, Noriszura Ismail
openaire   +1 more source

Robust estimation in the generalized poisson model

Statistics, 2004
A computationally simple method of robust estimation in the generalized Poisson model is presented. Estimators are proved to be optimal in the sense of local minimax testing, conditionally on the explanatory variable. Results of a Monte Carlo experiment are supplemented where robust and efficient estimators are compared.
openaire   +1 more source

Generalized Poisson–Lindley linear model for count data

Journal of Applied Statistics, 2016
ABSTRACTThe purpose of this paper is to develop a new linear regression model for count data, namely generalized-Poisson Lindley (GPL) linear model. The GPL linear model is performed by applying generalized linear model to GPL distribution. The model parameters are estimated by the maximum likelihood estimation.
Weerinrada Wongrin, Winai Bodhisuwan
openaire   +1 more source

General mixed Poisson regression models with varying dispersion

Statistics and Computing, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Barreto-Souza, Wagner, Simas, Alexandre B.   +1 more
openaire   +1 more source

Estimation in the Generalized Poisson Model via Robust Testing

Metrika, 2002
An estimation method is presented which compromises robust efficiency with computational feasibility in the case of the generalized Poisson model. The formal setup is built on flexible nonparametric extensions of the underlying model. The estimation efficiency is expressed via minimax properties of tests resulting from expansions of estimators.
openaire   +1 more source

Modelling of filariasis in East Java with Poisson regression and generalized Poisson regression models

AIP Conference Proceedings, 2016
Poisson regression has been used if the response variable is count data that based on the Poisson distribution. The Poisson distribution assumed equal dispersion. In fact, a situation where count data are over dispersion or under dispersion so that Poisson regression inappropriate because it may underestimate the standard errors and overstate the ...
openaire   +1 more source

On Periodic Generalized Poisson INAR(1) Model

Communications in Statistics - Simulation and Computation, 2023
Mohamed Bentarzi, Roufaida Souakri
openaire   +1 more source