Mean squared error comparisons of the modified ridge regression estimator and iiie restricted ridge regression estimator

1998 ◽  
Vol 27 (1) ◽  
pp. 131-138 ◽  
Author(s):  
Seiahatim Kaciranlar ◽  
Saduiiah Sakallioglu ◽  
Fikri Akdeniz
Keyword(s):  
Ridge Regression ◽  
Mean Squared Error ◽  
Regression Estimator ◽  
Squared Error ◽  
Ridge Regression Estimator

scholarly journals Modified Robust Ridge M-Estimators in Two-Parameter Ridge Regression Model

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Seyab Yasin ◽  
Sultan Salem ◽  
Hamdi Ayed ◽  
Shahid Kamal ◽  
Muhammad Suhail ◽  
...  
Keyword(s):  
Ridge Regression ◽  
Mean Squared Error ◽  
Least Square ◽  
Ridge Estimator ◽  
Least Square Estimator ◽  
Squared Error ◽  
Joint Problem ◽  
Ridge Regression Estimator ◽  
Simulation Results ◽  
Two Parameter

The methods of two-parameter ridge and ordinary ridge regression are very sensitive to the presence of the joint problem of multicollinearity and outliers in the y-direction. To overcome this problem, modified robust ridge M-estimators are proposed. The new estimators are then compared with the existing ones by means of extensive Monte Carlo simulations. According to mean squared error (MSE) criterion, the new estimators outperform the least square estimator, ridge regression estimator, and two-parameter ridge estimator in many considered scenarios. Two numerical examples are also presented to illustrate the simulation results.

scholarly journals Modified Ridge Regression Estimator with the Application of Peanut Production in Pakistan

2019 ◽  
pp. 1-8
Author(s):  
Asifa Mubeen ◽  
Nasir Jamal ◽  
Muhammad Hanif ◽  
Usman Shahzad
Keyword(s):  
Ridge Regression ◽  
Real Data ◽  
Production Data ◽  
Regression Estimator ◽  
Mean Square ◽  
Data Set ◽  
Regression Estimators ◽  
Peanut Production ◽  
Ridge Regression Estimator ◽  
The Mean

The main objective of the present study was to develop a new ridge regression estimator and fit the ridge regression model to the peanut production data of Pakistan. Peanut production data has been used to analyze the results. The data has been taken peanut production and growth rate of Pakistan. The mean square error of the proposed estimator is compared with some existing ridge regression estimators. In this study, we proposed a ridge regression estimator. The properties of proposed estimators are also discussed. The real data set of peanut production is used for assuming the performance of proposed and existing estimators. Numerical results of real data set show that proposed ridge regression estimator provides best results as compare to reviewed ones.

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