Title : ( On ridge parameter estimators under stochastic subspace hypothesis )
Authors: Mohammad Arashi , B. M. Golam Kibria , T. Valizadeh ,
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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.
Keywords
, MSE, restricted estimator, ridge regression, simulation study, subspace hypothesis
@article{paperid:1081577,
author = {Arashi, Mohammad and B. M. Golam Kibria and T. Valizadeh},
title = {On ridge parameter estimators under stochastic subspace hypothesis},
journal = {Journal of Statistical Computation and Simulation},
year = {2017},
volume = {87},
number = {5},
month = {March},
issn = {0094-9655},
pages = {966--983},
numpages = {17},
keywords = {MSE; restricted estimator; ridge regression; simulation study; subspace hypothesis},
}
%0 Journal Article
%T On ridge parameter estimators under stochastic subspace hypothesis
%A Arashi, Mohammad
%A B. M. Golam Kibria
%A T. Valizadeh
%J Journal of Statistical Computation and Simulation
%@ 0094-9655
%D 2017
