Results 11 to 20 of about 3,128,130 (383)
Poisson Regression with Survey Data
, 2014 We propose a way to remove the bias of a Poisson regression when the subjects are partially observed. In this paper we address this issue under certain assumptions about the missing-data generating process. We fix the total number of observed subjects and allow individual subjects to be observed randomly.
S. Jalil Kazemitabar
openalex +4 more sources
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
doaj +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
Estimating the change in soccer’s home advantage during the Covid-19 pandemic using bivariate Poisson regression [PDF]
AStA Advances in Statistical Analysis, 2020 In wake of the Covid-19 pandemic, 2019–2020 soccer seasons across the world were postponed and eventually made up during the summer months of 2020. Researchers from a variety of disciplines jumped at the opportunity to compare the rescheduled games ...
Luke S. Benz, Michael J. Lopez
semanticscholar +1 more source
A new estimator for the multicollinear Poisson regression model: simulation and application
Scientific Reports, 2021 The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM).
A. Lukman +3 more
semanticscholar +1 more source
Barekeng, 2022 Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression
M Al Haris, Prizka Rismawati Arum
doaj +1 more source
Modified ridge-type for the Poisson regression model: simulation and application
Journal of Applied Statistics, 2021 The Poisson regression model (PRM) is employed in modelling the relationship between a count variable (y) and one or more explanatory variables. The parameters of PRM are popularly estimated using the Poisson maximum likelihood estimator (PMLE). There is
A. Lukman +3 more
semanticscholar +1 more source
Evolutionary support vector regression for monitoring Poisson profiles
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2023 Many researchers have shown interest in profile monitoring; however, most of the applications in this field of research are developed under the assumption of normal response variable.
A. Yeganeh +4 more
semanticscholar +1 more source
Covid-19 Data Analysis in Tarakan with Poisson Regression and Spatial Poisson Process
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2023 COVID-19 entered Indonesia in March 2020 and included North Kalimantan Province, Tarakan. COVID-19 cases have outspread in Tarakan. The cause of the outspread and the patterns were not known yet. One relevant approach was to use Generalized Linear Models.
A'yunin Sofro +2 more
doaj +1 more source
Entropy, 2021 This study proposes a method for identifying and evaluating driving risk as a first step towards calculating premiums in the newly emerging context of usage-based insurance.
Shuai Sun +3 more
semanticscholar +1 more source