Results 271 to 280 of about 3,733,122 (330)

Understanding Poisson Regression

Journal of Nursing Education, 2014
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur.
Matthew J, Hayat, Melinda, Higgins
openaire   +2 more sources

On the James-Stein estimator for the poisson regression model

Communications in statistics. Simulation and computation, 2020
The Poisson regression model (PRM) aims to model a counting variable y, which is usually estimated by using maximum likelihood estimation (MLE) method. The performance of MLE is not satisfactory in the presence of multicollinearity. Therefore, we propose
M. Amin, M. Akram, M. Amanullah
semanticscholar   +1 more source

Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression

Journal of Transport Geography, 2019
Ridesourcing, or on-demand ridesharing, is quickly changing today's travel. Recently, research has linked socio-demographics to ridesourcing use. However, little of the research has focused on the impacts of built environment, an important factor to ...
Haitao Yu, Z. Peng
semanticscholar   +1 more source

Conway–Maxwell–Poisson regression models for dispersed count data

WIREs Computational Statistics, 2020
While Poisson regression serves as a standard tool for modeling the association between a count response variable and explanatory variables, it is well‐documented that this approach is limited by the Poisson model's assumption of data equi‐dispersion ...
Kimberly F. Sellers, Bailey Premeaux
semanticscholar   +1 more source

ADDRESSING IMBALANCED INSURANCE DATA THROUGH ZERO-INFLATED POISSON REGRESSION WITH BOOSTING

ASTIN Bulletin: The Journal of the International Actuarial Association, 2020
A machine learning approach to zero-inflated Poisson (ZIP) regression is introduced to address common difficulty arising from imbalanced financial data. The suggested ZIP can be interpreted as an adaptive weight adjustment procedure that removes the need
Simon C. K. Lee
semanticscholar   +1 more source

Modelling the impact of High Speed Rail on tourists with Geographically Weighted Poisson Regression

, 2020
In this paper the impact of High Speed Rail (HSR) on the tourism market is analysed. The original and added value of this contribution is in the proposed methodology, which considers the Geographically Weighted Regression technique, incorporated within a
F. Pagliara, F. Mauriello
semanticscholar   +1 more source

Poisson Regression

Event History Analysis with R, 2018
Göran Broström
openaire   +2 more sources

Double Poisson-Tweedie Regression Models

The International Journal of Biostatistics, 2019
AbstractIn this paper, we further extend the recently proposed Poisson-Tweedie regression models to include a linear predictor for the dispersion as well as for the expectation of the count response variable. The family of the considered models is specified using only second-moments assumptions, where the variance of the count response has the formμ ...
Ricardo R. Petterle, Wagner H. Bonat, Célestin C. Kokonendji, Juliane C. Seganfredo, Atamai Moraes, Monica G. da Silva   +5 more
openaire   +3 more sources

Improved two-parameter estimators for the negative binomial and Poisson regression models

Journal of Statistical Computation and Simulation, 2019
Negative binomial regression (NBR) and Poisson regression (PR) applications have become very popular in the analysis of count data in recent years. However, if there is a high degree of relationship between the independent variables, the problem of ...
Merve Kandemir Çetinkaya, Selahattin Kaçıranlar   +1 more
semanticscholar   +1 more source

Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data

Insurance, Mathematics & Economics, 2019
Customized personal rate offering is of growing importance in the insurance industry. To achieve this, an important step is to identify subgroups of insureds from the corresponding heterogeneous claim frequency data.
Kun Chen, Rui Huang, N. Chan, C. Yau
semanticscholar   +1 more source