Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in R [PDF]
Journal of Statistical Software, 2005 In this paper we present an R package called bivpois for maximum likelihood estimation of the parameters of bivariate and diagonal inflated bivariate Poisson regression models. An Expectation-Maximization (EM) algorithm is implemented.
Dimitris Karlis, Ioannis Ntzoufras
doaj +6 more sources
Southwest Respiratory and Critical Care Chronicles, 2015 This is a complicated subject that deals with predicting counts that cannot be handled by any other form of regression. Its methodology is described, as well as alternative methods of analysis that will need statistical consultation.
Shengping Yang, Gilbert Berdine
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The handling of overdispersion on Poisson regression model with the generalized Poisson regression model [PDF]
AIP Conference Proceedings, 2021 Regression model is used to model the relationship between predictor variables and response variable. In case that the response variable are Poisson distributed, Poisson regression model can be used to model the relationship. An assumption that must be fulfilled on Poisson distribution is the mean value of data equals to the variance value (or so ...
Dewi Retno Sari Saputro +2 more
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Variable Selection for Poisson Regression Model [PDF]
, 2003 Poisson regression is useful in modeling count data. In a study with many independent variables, it is desirable to reduce the number of variables while maintaining a model that is useful for prediction.
Akaike, Efroymson, Merkle
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A Poisson Ridge Regression Estimator [PDF]
Economic Modelling, 2011 The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression
Månsson, Kristofer, Shukur, Ghazi
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Perbandingan Regresi Binomial Negatif dan Regresi Conway-Maxwell-Poisson dalam Mengatasi Overdispersi pada Regresi Poisson [PDF]
Jurnal Gantang, 2017 Regresi Binomial Negatif dan regresi Conway-Maxwell-Poisson merupakan solusi untuk mengatasi overdispersi pada regresi Poisson. Kedua model tersebut merupakan perluasan dari model regresi Poisson.
Lusi Eka Afri
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On bivariate Poisson regression models
Journal of King Saud University - Science, 2015 AbstractIn this paper, we consider estimating the parameters of bivariate and zero-inflated bivariate Poisson regression models using the conditional method. This method is compared with the standard method, which uses the joint probability function. Simulations and real applications show that the two methods have almost identical Akaike Information ...
Fatimah E. Almuhayfith +2 more
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Comparison of univariate and bivariate Poisson regression methods in the analysis of determinants of female schooling and fertility in Malawi [PDF]
BMC Public HealthRecent research has established existence of a correlation between women’s education and fertility, suggesting that they share similar risk factors. However, in many studies, the two variables were analysed separately, which could bias the conclusions by
Eneles Mponda, Tsirizani Mwalimu Kaombe
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Mean-parametrized Conway-Maxwell-Poisson regression models for dispersed counts [PDF]
, 2017 Conway-Maxwell-Poisson (CMP) distributions are flexible generalizations of the Poisson distribution for modelling overdispersed or underdispersed counts.
Huang, Alan
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Locally kernel weighted maximum likelihood estimator for local linear multi-predictor poisson regression [PDF]
MethodsXWe introduce a new multi-predictor regression model based on the Poisson distribution using a local linear approach called the local linear multi-predictor Poisson regression.
Darnah +13 more
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