Modelling Generalized Poisson Regression in the Number of Dengue Hemorrhagic Fever (DHF) in East Nusa Tenggara [PDF]
E3S Web of Conferences, 2020 Regression analysis is an analysis used to model the relationship between the dependent variable (Y) and the independent variable (X). If the dependent variable is a discrete random variable, it is developed using the Poisson regression model.
Prahutama Alan +2 more
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Axioms, 2022 The Poisson maximum likelihood (PML) is used to estimate the coefficients of the Poisson regression model (PRM). Since the resulting estimators are sensitive to outliers, different studies have provided robust Poisson regression estimators to alleviate ...
Issam Dawoud +3 more
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Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Czado, Claudia, Min, Aleksey
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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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Forecasting Daily Wildfire Activity Using Poisson Regression
IEEE Transactions on Geoscience and Remote Sensing, 2020 Wildfires and their emissions reduce air quality in many regions of the world, contributing to thousands of premature deaths each year. Smoke forecasting systems have the potential to improve health outcomes by providing future estimates of surface ...
Casey A. Graff +5 more
semanticscholar +1 more source
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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Introducing and evaluating a Gibbs sampler for spatial Poisson regression models [PDF]
, 2005 In this paper we present a Gibbs sampler for a Poisson model including spatial effects. Frühwirth-Schnatter und Wagner (2004b) show that by data augmentation via the introduction of two sequences of latent variables a Poisson regression model can be ...
Czado, Claudia, Gschlößl, Susanne
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Chapter 20: What do interviewers learn? Changes in interview length and interviewer behaviors over the field period. Appendix 20 [PDF]
, 2020 Appendix 20A Full Model Coefficients and Standard Errors Predicting Count of Questions with Individual Interviewer Behaviors, Two-level Multilevel Poisson Models with Number of Questions Asked as Exposure Variable, WLT1 and WLT2 Analytic strategyTable ...
Olson, Kristen M., Smyth, Jolene
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PEMODELAN JUMLAH KEMATIAN BAYI DI PROVINSI MALUKU TAHUN 2010 DENGAN MENGGUNAKAN REGRESI POISSON
Barekeng, 2012 Infant mortality is an experienced child death before the age of one year. Regression analysis is a statistical analysis that aims to model the relationship between response variables (Y) with predictor variables (X).
Salmon N. Aulele
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Perbandingan Regresi Binomial Negatif dan Regresi Conway-Maxwell-Poisson dalam Mengatasi Overdispersi pada Regresi Poisson [PDF]
, 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.
Afri, L. E. (Lusi)
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