Results 11 to 20 of about 5,788,827 (317)
Modified One-Parameter Liu Estimator for the Linear Regression Model
Modelling and Simulation in Engineering, 2020 Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman +3 more
doaj +2 more sources
Short period PM2.5 prediction based on multivariate linear regression model. [PDF]
PLoS ONE, 2018 A multivariate linear regression model was proposed to achieve short period prediction of PM2.5 (fine particles with an aerodynamic diameter of 2.5 μm or less).
Rui Zhao +4 more
doaj +2 more sources
Prediction of Gene Expression Patterns With Generalized Linear Regression Model
Frontiers in Genetics, 2019 Cell reprogramming has played important roles in medical science, such as tissue repair, organ reconstruction, disease treatment, new drug development, and new species breeding.
Shuai Liu +6 more
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A New Ridge-Type Estimator for the Linear Regression Model: Simulations and Applications. [PDF]
Scientifica (Cairo), 2020 The ridge regression-type (Hoerl and Kennard, 1970) and Liu-type (Liu, 1993) estimators are consistently attractive shrinkage methods to reduce the effects of multicollinearity for both linear and nonlinear regression models.
Kibria BMG, Lukman AF.
europepmc +2 more sources
Diabetes & metabolic syndrome, 2020 Introduction and Aims The COVID-19 pandemic originated from the city of Wuhan of China has highly affected the health, socio-economic and financial matters of the different countries of the world.
Smita Rath +2 more
semanticscholar +1 more source
A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
Stats, 2020 In a multiple linear regression model, the ordinary least squares estimator is inefficient when the multicollinearity problem exists. Many authors have proposed different estimators to overcome the multicollinearity problem for linear regression models ...
I. Dawoud, B. M. G. Kibria
semanticscholar +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
Varying-coefficient functional linear regression [PDF]
, 2010 Functional linear regression analysis aims to model regression relations which include a functional predictor. The analog of the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a ...
Fan, Jianqing +2 more
core +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
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