Results 1 to 10 of about 143,004 (295)

A Poisson ridge regression estimator

Economic Modelling, 2011
The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity.
Kristofer Mansson, Ghazi Shukur
exaly   +4 more sources

Poisson regression [PDF]

American Journal of Orthodontics and Dentofacial Orthopedics, 2017
In this article, we will describe how to analyze the data used in our previous article1 regarding implant failures with Poisson regression. We are interested in examining whether the rate of implant failure is different between smokers and nonsmokers. In
Despina Koletsi, Pandis, Nikolaos, Koletsi, D, Nikolaos Pandis   +3 more
core   +4 more sources

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
doaj   +4 more sources

Poisson Regression [PDF]

Southwest Respiratory and Critical Care Chronicles, 2015
Shengping Yang, Gilbert Berdine
doaj   +7 more sources

Robust designs for poisson regression models [PDF]

Technometrics, 2011
We consider the problem of how to construct robust designs for Poisson regression models. An analytical expression is derived for robust designs for first-order Poisson regression models where uncertainty exists in the prior parameter estimates.Given ...
Eccleston, John, McGree, James M., Eccleston, John A., McGree, James Matthew   +3 more
core   +5 more sources

Comparison of univariate and bivariate Poisson regression methods in the analysis of determinants of female schooling and fertility in Malawi [PDF]

BMC Public Health
Recent research has established existence of a correlation between women’s education and fertility, suggesting that they share similar risk factors. However, in many studies, the two variables were analysed separately, which could bias the conclusions by
Eneles Mponda, Tsirizani Mwalimu Kaombe
doaj   +2 more sources

Locally kernel weighted maximum likelihood estimator for local linear multi-predictor poisson regression [PDF]

MethodsX
We introduce a new multi-predictor regression model based on the Poisson distribution using a local linear approach called the local linear multi-predictor Poisson regression.
Darnah, Memi Nor Hayati, Sri Wahyuningsih, Iriyani Kamaruddin, Suyitno, Andrea Tri Rian Dani, Rito Goejantoro, Desi Yuniarti, Fidia Deny Tisna Amijaya, Ika Purnamasari, Meiliyani Siringoringo, Surya Prangga, Ratna Kusuma, Rahmawati Munir   +13 more
doaj   +2 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

Secure Poisson Regression [PDF]

IACR Cryptol. ePrint Arch., 2021
We introduce the first construction for secure two-party computation of Poisson regression, which enables two parties who hold shares of the input samples to learn only the resulting Poisson model while protecting the privacy of the inputs.
Karn Seth, Mahimna Kelkar, Mariana Raykova, Phi Hung Le   +3 more
core   +3 more sources

NEGATIVE BINOMIAL REGRESSION AND GENERALIZED POISSON REGRESSION MODELS ON THE NUMBER OF TRAFFIC ACCIDENTS IN CENTRAL JAVA

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