Results 11 to 20 of about 33,887 (293)
New ridge parameter estimators for the quasi-Poisson ridge regression model
Scientific ReportsThe quasi-Poisson regression model is used for count data and is preferred over the Poisson regression model in the case of over-dispersed count data.
Aamir Shahzad +3 more
doaj +3 more sources
A Poisson Ridge Regression Estimator [PDF]
Economic Modelling, 2011 The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression
Månsson, Kristofer, Shukur, Ghazi
core +3 more sources
Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation [PDF]
Surveys in Mathematics and its Applications, 2009 Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR).
Sharad Damodar Gore, Feras Sh. M. Batah
doaj +2 more sources
Polynomial ridge flowfield estimation [PDF]
Physics of Fluids, 2021 Computational fluid dynamics plays a key role in the design process across many industries. Recently, there has been increasing interest in data-driven methods in order to exploit the large volume of data generated by such computations. This paper introduces the idea of using spatially correlated polynomial ridge functions for rapid flowfield ...
A. Scillitoe +3 more
openaire +2 more sources
Smoothly adaptively centered ridge estimator [PDF]
Journal of Multivariate Analysis, 2022 With a focus on linear models with smooth functional covariates, we propose a penalization framework (SACR) based on the nonzero centered ridge, where the center of the penalty is optimally reweighted in a supervised way, starting from the ordinary ridge solution as the initial centerfunction.
openaire +3 more sources
A New Tobit Ridge-Type Estimator of the Censored Regression Model With Multicollinearity Problem
Frontiers in Applied Mathematics and Statistics, 2022 In the censored regression model, the Tobit maximum likelihood estimator is unstable and inefficient in the occurrence of the multicollinearity problem.
Issam Dawoud +3 more
doaj +1 more source
Superiority of the MCRR Estimator Over Some Estimators In A Linear Model [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 Modified (r, k) class ridge regression (MCRR) which includes unbiased ridge regression (URR), (r, k) class, principal components regression (PCR) and the ordinary least squares (OLS) estimators is proposed in regression analysis, to overcome the problem ...
Feras Sh. M. Batah
doaj +1 more source
A new hybrid estimator for linear regression model analysis: Computations and simulations
Scientific African, 2023 The Linear regression model explores the relationship between a response variable and one or more independent variables. The parameters in the model are often estimated using the Ordinary Least Square Estimator (OLSE).
G.A. Shewa, F.I. Ugwuowo
doaj +1 more source
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2018 The useof biased estimation techniques is inevitable in connection withmulticollinearity. Two stage ridge estimator is a pioneer biased estimatorwhich is use to recover the problems that are originated from themulticollinearity.
Selma Toker, Nimet Özbay
doaj +1 more source
Alexandria Engineering Journal, 2023 The Poisson Inverse Gaussian Regression model (PIGRM) is used for modeling the count datasets to deal with the issue of over-dispersion. Generally, the maximum likelihood estimator (MLE) is used to estimate the PIGRM estimates.
Asia Batool +2 more
doaj +1 more source