Volume 15, Number 2 (8-2016)                   JIRSS 2016, 15(2): 87-103 | Back to browse issues page



DOI: 10.18869/acadpub.jirss.15.2.87

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ghapani F, Babadi B. A New Ridge Estimator in Linear Measurement Error Model with Stochastic Linear Restrictions . JIRSS. 2016; 15 (2) :87-103
URL: http://jirss.irstat.ir/article-1-360-en.html

Department of Mathematic and statistics, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran
Abstract:   (2089 Views)

In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against the ME are examined in terms of the mean squared error matrix sense. Finally, a numerical example and a Monte Carlo simulation are also given to show the theoretical resultsIn this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against the ME are examined in terms of the mean squared error matrix sense. Finally, a numerical example and a Monte Carlo simulation are also given to show the theoretical resultsIn this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against the ME are examined in terms of the mean squared error matrix sense. Finally, a numerical example and a Monte Carlo simulation are also given to show the theoretical resultsIn this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against the ME are examined in terms of the mean squared error matrix sense. Finally, a numerical example and a Monte Carlo simulation are also given to show the theoretical results.

Full-Text [PDF 111 kb]   (470 Downloads)    
Type of Study: Original Paper | Subject: 62Jxx: Linear inference, regression
Received: 2016/06/11 | Accepted: 2016/08/25 | Published: 2016/08/25

Add your comments about this article : Your username or email:
Write the security code in the box

Send email to the article author


© 2015 All Rights Reserved | Journal of The Iranian Statistical Society