Estimate the Slope Parameter in Replicated Linear Structural Relationship Model

Amel Saad Alshargawi, Abdul Ghapor Hussin, Ummul Fahri binti Abd Rauf

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.

 


Keywords


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

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References


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

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