On ridge parameter estimators under stochastic subspace hypothesis. Issue 5 (24th March 2017)

• Record Type: Journal Article
• Authors: Arashi, M.; Kibria, B. M. Golam; Valizadeh, T.
• Is Part Of: Journal of statistical computation and simulation. Volume 87:Issue 5(2017)
• Page Start: 966
• Page End: 983
• Publication Date: 2017-03-24
• Subjects: MSE -- restricted estimator -- ridge regression -- simulation study -- subspace hypothesis; 62J05 -- 62J07 -- 62F10; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2016.1239104
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: This paper considers several estimators for estimating the restricted ridge parameter estimators. A simulation study has been conducted to compare the performance of these estimators. Based on the simulation study we found that, increasing the correlation between the independent variables has positive effect on the mean square error (MSE). However, increasing the value of ρ has negative effect on MSE. When the sample size increases, the MSE decreases even when the correlation between the independent variables is large. Two real life examples have been considered to illustrate the performance of the estimators.