Estimate the Slope Parameter in Replicated Linear Structural Relationship Model

Authors

  • Amel Saad Alshargawi Defence University of Malaysia, Kuala Lumpur, UPNM
  • Abdul Ghapor Hussin
  • Ummul Fahri binti Abd Rauf

DOI:

https://doi.org/10.24203/ajas.v7i1.5675

Keywords:

Maximum likelihood method, A nonparametric method, Trimmed mean, Outlier, Linear structural relationship model with replicated

Abstract

Replication of observation allows consistent estimation of slope parameter of a linear structural model when the ratio of variances is unknown or when some external information about parameters is not available. In this paper, we look at the way a linear structural relationship model work by replicating observations with two different estimation methods of slope parameter and different cases of existence of outliers. The maximum likelihood estimate (MLE) and a new nonparametric robust estimation method  are used to estimate the slope parameter in replicated linear structural relationship model (RLSRM). The simulation studies and the application of real data are used to investigate the performance of the estimated parameters.

 

References

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Published

2019-02-22

How to Cite

Alshargawi, A. S., Hussin, A. G., & Abd Rauf, U. F. binti. (2019). Estimate the Slope Parameter in Replicated Linear Structural Relationship Model. Asian Journal of Applied Sciences, 7(1). https://doi.org/10.24203/ajas.v7i1.5675

Issue

Vol. 7 No. 1 (2019): February 2019

Section

Articles

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