Subscribe Now Subscribe Today
Science Alert
 
FOLLOW US:     Facebook     Twitter
Blue
   
Curve Top
Asian Journal of Mathematics & Statistics
  Year: 2010 | Volume: 3 | Issue: 2 | Page No.: 82-92
DOI: 10.3923/ajms.2010.82.92
Efficient Wald Type Estimators for Simple Linear Measurement Error Model
A. Al-Radaideh, A. Al-Nasser and E. Ciavolino

Abstract:
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.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    On Using the Maximum Entropy Median for Fitting the Unreplicated Functional Model Between the Unemployment Rate and the Human Development Index in the Arab States
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

URL: https://scialert.net/abstract/?doi=ajms.2010.82.92

 
COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

       

       

Curve Bottom