Results 1 to 10 of about 33,950 (290)

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   +4 more sources

Robust modified jackknife ridge estimator for the Poisson regression model with multicollinearity and outliers

Scientific African, 2022
The parameters in the Poisson regression model are usually estimated using the maximum likelihood estimator (MLE). MLE suffers a breakdown when there is either multicollinearity or outliers in the Poisson regression model.
Kingsley C Arum, Fidelis I Ugwuowo, Henrietta E Oranye   +2 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

A New Mixed Biased Estimator for Ill‐Conditioning Challenges in Linear Regression Model With Chemometrics Applications [PDF]

Analytical Science Advances
In linear regression models, the ordinary least squares (OLS) method is used to estimate the unknown regression coefficients. However, the OLS estimator may provide unreliable estimates in non‐orthogonal models.
Muhammad Amin, Sadiah M. A. Aljeddani, Muhammad Nauman Akram, Sajida Yasmeen   +3 more
doaj   +2 more sources

A bias-reduced estimator for generalized Poisson regression with application to carbon dioxide emission in Canada [PDF]

Scientific Reports
The generalized Poisson regression model (GPRM) provides a flexible framework for modeling count data, especially those exhibiting over- or underdispersion.
Fatimah M. Alghamdi, Ahmed M. Gemeay, Gamal A. Abd-Elmougod, Ehab M. Almetwally, M. A. El-Qurashi, Getachew Tekle Mekiso, Ali T. Hammad   +6 more
doaj   +2 more sources

Stochastic Restricted Biased Estimators in Misspecified Regression Model with Incomplete Prior Information

Journal of Probability and Statistics, 2018
The analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multicollinearity exists among the explanatory variables. The Stochastic Restricted Ridge Estimator (SRRE), Stochastic Restricted Almost
Manickavasagar Kayanan, Pushpakanthie Wijekoon   +1 more
doaj   +3 more sources

New ridge parameter estimators for the quasi-Poisson ridge regression model

Scientific Reports
The 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, Muhammad Amin, Walid Emam, Muhammad Faisal   +3 more
doaj   +3 more sources

New robust estimator for handling outliers and multicollinearity in gamma regression model with application to breast cancer data [PDF]

Scientific Reports
The gamma regression model (GRM) is commonly used to analyze continuous data that are positively skewed. However, the GRM is sensitive to multicollinearity and outliers. These two problems often occur in regression analysis.
Arwa M. Alshangiti, Ahmed M. Gemeay, Mahmoud E. Bakr, Abdirashid M. Yousuf, M. A. El-Qurashi, Oluwafemi Samson Balogun, Eslam Hussam, Ali T. Hammad   +7 more
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, P. Seshadri, C. Y. Wong, A. Duncan   +3 more
openaire   +2 more sources

Modified Jackknifed Ridge Estimator in Bell Regression Model: Theory, Simulation and Applications

Iraqi Journal for Computer Science and Mathematics, 2023
Regression models explore the relationship between the response variable and one or more explanatory variables. It becomes practically challenging in real-life applications to model this relationship when the explanatory variables are linearly dependent.
Zakariya Algamal, Adewale Lukman, B. M. Kibria Golam, Arowolo Taofik   +3 more
doaj   +1 more source