The generalized preliminary test estimator when different sets of stochastic restrictions are available

The generalized preliminary test estimator when different sets of stochastic restrictions are... Arumairajan and Wijekoon (Commun Stat—Theor Methods, in press, 2014) proposed a generalized preliminary test stochastic restricted estimator (GPTSRE) to represent the preliminary test estimators when stochastic restrictions are available in addition to sample model. The aim of this paper is to define the GPTSRE when two different sets of competing stochastic restrictions are available. Moreover the conditions for superiority of GPTSRE based on one stochastic restriction over the other are derived with respect to mean square error (MSE) matrix criterion. Furthermore the estimator GPTSRE is theoretically compared with almost unbiased ridge estimator and almost unbiased Liu estimator in the MSE matrix sense. Finally a Monte Carlo simulation study and numerical example are done to illustrate the theoretical findings. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Statistical Papers Springer Journals

The generalized preliminary test estimator when different sets of stochastic restrictions are available

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2015 by Springer-Verlag Berlin Heidelberg
Subject
Statistics; Statistics for Business/Economics/Mathematical Finance/Insurance; Probability Theory and Stochastic Processes; Economic Theory/Quantitative Economics/Mathematical Methods; Operations Research/Decision Theory
ISSN
0932-5026
eISSN
1613-9798
D.O.I.
10.1007/s00362-015-0723-x
Publisher site
See Article on Publisher Site

Abstract

Arumairajan and Wijekoon (Commun Stat—Theor Methods, in press, 2014) proposed a generalized preliminary test stochastic restricted estimator (GPTSRE) to represent the preliminary test estimators when stochastic restrictions are available in addition to sample model. The aim of this paper is to define the GPTSRE when two different sets of competing stochastic restrictions are available. Moreover the conditions for superiority of GPTSRE based on one stochastic restriction over the other are derived with respect to mean square error (MSE) matrix criterion. Furthermore the estimator GPTSRE is theoretically compared with almost unbiased ridge estimator and almost unbiased Liu estimator in the MSE matrix sense. Finally a Monte Carlo simulation study and numerical example are done to illustrate the theoretical findings.

Journal

Statistical PapersSpringer Journals

Published: Nov 9, 2015

References

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