A STOCHASTIC RESTRICTED MODIFIED (r, K) CLASS RIDGE REGRESSION ESTIMATOR IN THE LINEAR MODEL

2018 ◽  
Vol 105 (2) ◽  
pp. 131-153
Author(s):  
El Houssainy A. Rady ◽  
Salah M. Mohamed ◽  
Alaa A. Abd Elmegaly
Keyword(s):  
Linear Model ◽  
Ridge Regression ◽  
Regression Estimator ◽  
Ridge Regression Estimator

scholarly journals Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation

2019 ◽  
Vol 16 (4) ◽  
pp. 0918
Author(s):  
Saja Mohammad Hussein
Keyword(s):  
Linear Model ◽  
Ridge Regression ◽  
Linear Part ◽  
Partially Linear Model ◽  
Partial Linear Model ◽  
Regression Estimator ◽  
Nonlinear Part ◽  
Partially Linear ◽  
Ridge Regression Estimator ◽  
The Difference

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

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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