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Asian Journal of Mathematics & Statistics
  Year: 2010 | Volume: 3 | Issue: 2 | Page No.: 82-92
DOI: 10.3923/ajms.2010.82.92
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Efficient Wald Type Estimators for Simple Linear Measurement Error Model

A. Al-Radaideh, A. Al-Nasser and E. Ciavolino

In this study, a new sampling technique called L Ranked Set Sampling (LRSS) was used to estimate the Error in Variable Model (EIV) parameter using Wald-type estimators. The new estimators were made in order to reduce the cost and increase the efficiency of the estimators. The new formulas of the Wald type estimators are shown to be unbiased towards the EIV model and are evaluated by comparing LRSS with Simple Random Sampling (SRS) and Ranked Set Sampling (RSS). Two Monte Carlo experiments were considered to study the performance of Wald-type estimators with the three sampling techniques. It appears that the suggested estimators based on LRSS are more accurate and more efficient. Moreover, a real data set of student achievements is studied.
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How to cite this article:

A. Al-Radaideh, A. Al-Nasser and E. Ciavolino, 2010. Efficient Wald Type Estimators for Simple Linear Measurement Error Model. Asian Journal of Mathematics & Statistics, 3: 82-92.

DOI: 10.3923/ajms.2010.82.92






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