Improvement of the Preliminary Test Estimator When Stochastic Restrictions are Available in Linear Regression Model

ISSN Print: 2161-718X
ISSN Online: 2161-7198
www.scirp.net/journal/ojs
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Citations

"Improvement of the Preliminary Test Estimator When Stochastic Restrictions are Available in Linear Regression Model"
written by Sivarajah Arumairajan, Pushpakanthie Wijekoon,
published by Open Journal of Statistics, Vol.3 No.4, 2013

has been cited by the following article(s):

[1]	Robust estimation in restricted linear regression
	2019

[2]	Generalized preliminary test stochastic restricted estimator in the linear regression model
	Communications in Statistics-Theory and Methods, 2016

[3]	Shapley value regression and the resolution of multicollinearity
	SSRN, 2016

[4]	Principal Component Preliminary Test Estimator in the Linear Regression Model
	2016

[5]	Preliminary Test Stochastic Restricted rk Class Estimator and Preliminary Test Stochastic Restricted rd Class Estimator in Linear Regression Model
	British Journal of Mathematics & Computer Science, 2015

[6]	More on the Preliminary Test Stochastic Restricted Liu Estimator in Linear Regression Model
	Open Journal of Statistics, 2015

[7]	The generalized preliminary test estimator when different sets of stochastic restrictions are available
	Statistical Papers, 2015

[1]	Robust estimation in restricted linear regression Communications in Statistics - Simulation and Computation, 2022 DOI:10.1080/03610918.2019.1661475

[2]	The generalized preliminary test estimator when different sets of stochastic restrictions are available Statistical Papers, 2017 DOI:10.1007/s00362-015-0723-x

[3]	Generalized preliminary test stochastic restricted estimator in the linear regression model Communications in Statistics - Theory and Methods, 2016 DOI:10.1080/03610926.2014.957850

[4]	Shapley Value Regression and the Resolution of Multicollinearity SSRN Electronic Journal , 2016 DOI:10.2139/ssrn.2797224

[5]	More on the Preliminary Test Stochastic Restricted Liu Estimator in Linear Regression Model Open Journal of Statistics, 2015 DOI:10.4236/ojs.2015.54035