Results 11 to 20 of about 111,400 (254)
Bayesian regression of piecewise homogeneous Poisson processes [PDF]
Papers in Physics, 2015 In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data.
Diego Sevilla
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Modelling children ever born using performance evaluation metrics: A dataset
Data in Brief, 2021 Predicting the number of total children ever born in a country is a key component for proper implementation of economic growth policy. Here, performance metrics were used to predict models that appropriately describe the factors that affect children ever
Jecinta U. Ibeji +3 more
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Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in R
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.
Ioannis Ntzoufras, Dimitris Karlis
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E-Jurnal Matematika, 2013 The Poisson regression is generally used to analyze the response variable that is a discrete data. Poisson regression has assumption which must be met, that is condition equidispersion.
I PUTU YUDANTA EKA PUTRA +2 more
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POISSON REGRESSION MODELLING OF AUTOMOBILE INSURANCE USING R
Barekeng, 2022 Automobile insurance benefits are protecting the vehicle and minimizing customer losses. Insurance companies must provide funds to pay customer claims if a claim occurs. Insurance claims can be modelled by Poisson regression.
Sandy Vantika +2 more
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E-Jurnal Matematika, 2014 Poisson regression is a nonlinear regression that is often used to model count response variable and categorical, interval, or count regressor. This regression assumes equidispersion, i.e., the variance equals the mean.
NI MADE RARA KESWARI +2 more
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The handling of overdispersion on Poisson regression model with the generalized Poisson regression model [PDF]
AIP Conference Proceedings, 2021 Regression model is used to model the relationship between predictor variables and response variable. In case that the response variable are Poisson distributed, Poisson regression model can be used to model the relationship. An assumption that must be fulfilled on Poisson distribution is the mean value of data equals to the variance value (or so ...
Dewi Retno Sari Saputro +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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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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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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