On the Performance of Jackknife Based Estimators for Ridge Regression

On the Performance of Jackknife Based Estimators for Ridge Regression

Regression techniques are generally used to predict a response variable using one or more predictor variables. In many fields of study, the regressors can be highly intercorrelated, which leads to the problem of multicollinearity. Consequently, the ordinary least squares estimates become inconsisten...

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Bibliographic Details
Main Authors: Ismail Shah, Faiza Sajid, Sajid Ali, Amjad Rehman, Saeed Ali Bahaj, Suliman Mohamed Fati
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Ridge regression
multicollinearity
Monte Carlo simulations
mean squared error
Jackknife technique
machine learning
Online Access:https://ieeexplore.ieee.org/document/9422703/

Internet

https://ieeexplore.ieee.org/document/9422703/

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