Southwest Respiratory and Critical Care Chronicles, 2015 Poisson regression is a form of a generalized linear model where the response variable is modeled as having a Poisson distribution. The Poisson distribution models random variables with non-negative integer values.
Shengping Yang, Gilbert Berdine
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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 +4 more sources
Modelling fertility levels in Nigeria using Generalized Poisson regression-based approach
Scientific African, 2020 The rapid increase in total children ever born without a proportionate growth in the Nigerian economy has been a major concern. The total children ever born, being a count data, requires applying an appropriate regression model.
Jecinta U. Ibeji +3 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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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) method.
Månsson, Kristofer, Shukur, Ghazi
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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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Poisson regression model with change points [PDF]
Journal of Applied Research on Industrial Engineering, 2021 There are many different fields the change point analysis arises. In those cases, the main problem is locating the unknown change points. The aim of this study is to detect location and time of change point in Poisson regression model.
Reza Habibi
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Robust biased estimators for Poisson regression model: Simulation and applications
Concurrency and Computation, 2023 The method of maximum likelihood flops when there is linear dependency (multicollinearity) and outlier in the generalized linear models. In this study, we combined the ridge estimator with the transformed M‐estimator (MT) and the conditionally unbiased ...
A. Lukman, M. Arashi, V. Prokaj
semanticscholar +1 more source
Efficient Posterior Sampling for Bayesian Poisson Regression [PDF]
Journal of Computational And Graphical Statistics, 2021 Poisson log-linear models are ubiquitous in many applications, and one of the most popular approaches for parametric count regression. In the Bayesian context, however, there are no sufficient specific computational tools for efficient sampling from the ...
Laura D'angelo, A. Canale
semanticscholar +1 more source
Zero-Inflated Generalized Poisson Regression Model with an Application to Domestic Violence Data
Journal of Data Science, 2021 The generalized Poisson regression model has been used to model dispersed count data. It is a good competitor to the negative binomial re- gression model when the count data is over-dispersed.
F. Famoye, Karan P. Singh
semanticscholar +1 more source