Results 1 to 10 of about 2,678,398 (281)
Modified Unbiased Optimal Estimator For Linear Regression Model [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2023 In this paper, we propose a novel form of Generalized Unbiased Optimal Estimator where the explanatory variables are multicollinear. The proposed estimator's bias, variance, and mean square error matrix (MSE) are calculated.
Hussein AL-jumaili, Mustafa Alheety
doaj +1 more source
Bayesian linear regression model for method comparison studies
Ceylon Journal of Science, 2022 Method comparison is an essential area related to clinical science and study to compare a new method with an existing method to check if a new one can replace with an existing method.
S.M.M. Lakmali +2 more
doaj +1 more source
Robust Model Selection in Linear regression [PDF]
Kirkuk Journal of Science, 2007 The research deals with the proposing of robust formula for the accumulate prediction error (APE) criterion which is used in selecting regression model. The proposed formula evaluated with a simulation study.
Dr. Sabah Haseeb Hassan
doaj +1 more source
Kuwait Journal of Science, 2023 Ridge regression is employed to estimate the regression parameters while circumventing the multicollinearity among independent variables. The ridge parameter plays a vital role as it controls bias-variance tradeoff. Several methods for choosing the ridge
Irum Sajjad Dar +3 more
doaj +1 more source
A Linear Regression Thermal Displacement Lathe Spindle Model
Energies, 2020 Thermal error is one of the main reasons for the loss of accuracy in lathe machining. In this study, a thermal deformation compensation model is presented that can reduce the influence of spindle thermal error on machining accuracy.
Chih-Jer Lin +5 more
doaj +1 more source
Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model
The Scientific World Journal, 2020 The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to estimate its parameter.
Adewale F. Lukman +3 more
doaj +1 more source
Study of Some Kinds of Ridge Regression Estimators in Linear Regression Model
Tikrit Journal of Pure Science, 2020 In linear regression model, the biased estimation is one of the most commonly used methods to reduce the effect of the multicollinearity. In this paper, a simulation study is performed to compare the relative efficiency of some kinds of biased ...
Mustafa Nadhim Lattef, Mustafa I ALheety
doaj +1 more source
M Robust Weighted Ridge Estimator in Linear Regression Model
African Scientific Reports, 2023 Correlated regressors are a major threat to the performance of the conventional ordinary least squares (OLS) estimator. The ridge estimator provides more stable estimates in this circumstance.
Taiwo Stephen Fayose +2 more
doaj +1 more source
Structural Change Analysis in Linear Regression Model.
Revista de Matemática: Teoría y Aplicaciones, 2010 Assuming that the observations are from normal distribution we obtain de distribution of the maximum likelihood ratio test if there is a change in the parameters at an unknown time and we find the maximum likehood estimators of the time change too.
Blanca Rosa Pérez Salvador +1 more
doaj +1 more source
Stochastic Restricted LASSO-Type Estimator in the Linear Regression Model
Journal of Probability and Statistics, 2020 Among several variable selection methods, LASSO is the most desirable estimation procedure for handling regularization and variable selection simultaneously in the high-dimensional linear regression models when multicollinearity exists among the ...
Manickavasagar Kayanan +1 more
doaj +1 more source