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BMC Medical Research Methodology, 2018 BackgroundLog-binomial and robust (modified) Poisson regression models are popular approaches to estimate risk ratios for binary response variables. Previous studies have shown that comparatively they produce similar point estimates and standard errors ...
Wansu Chen +3 more
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Jackknifed Liu-type Estimator in Poisson Regression Model
, 2020 The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data.
Ahmed Alkhateeb, Z. Algamal
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Boosting Poisson regression models with telematics car driving data
Machine-mediated learning, 2020 With the emergence of telematics car driving data, insurance companies have started to boost classical actuarial regression models for claim frequency prediction with telematics car driving information.
Guangyuan Gao, He Wang, M. Wüthrich
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Poisson regression analysis of ungrouped data [PDF]
Occupational and Environmental Medicine, 2005 Background:Poisson regression is routinely used for analysis of epidemiological data from studies of large occupational cohorts. It is typically implemented as a grouped method of data analysis in which all exposure and covariate information is categorised and person-time and events are tabulated.Aims:To describe an alternative approach to Poisson ...
David B. Richardson +2 more
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A flexible regression model for count data
, 2010 Poisson regression is a popular tool for modeling count data and is applied in a vast array of applications from the social to the physical sciences and beyond.
Sellers, Kimberly F., Shmueli, Galit
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Poisson regression charts for the monitoring of surveillance time series [PDF]
, 2006 This paper presents a Poisson control chart for monitoring time series of counts typically arising in the surveillance of infectious diseases. The in-control mean is assumed to be time-varying and linear on the log-scale with intercept and seasonal ...
Höhle, Michael
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PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON
E-Jurnal Matematika, 2013 Poisson regression was used to analyze the count data which Poisson distributed. Poisson regression analysis requires state equidispersion, in which the mean value of the response variable is equal to the value of the variance.
PUTU SUSAN PRADAWATI +2 more
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EM Estimation for Zero- and k-Inflated Poisson Regression Model
Computation, 2021 Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the
Monika Arora, N. Rao Chaganty
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IJAIN (International Journal of Advances in Intelligent Informatics), 2016 Poisson distribution is one of discrete distribution that is often used in modeling of rare events. The data obtained in form of counts with non-negative integers. One of analysis that is used in modeling count data is Poisson regression.
Lili Puspita Rahayu +2 more
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PLoS ONE, 2022 In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and computational efficiency.
Daisuke Murakami, Tomoko Matsui
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