The Comparison Between Maximum Weighted and Trimmed Likelihood Estimator of The Simple Circular Regression Model

Authors

Ehab A. Mahmood, University of Babylon, IraqFollow
Habshah Midi, University Putra Malaysia, Serdang, Malaysia
Abdul Ghapor Hussin, National Defense University of Malaysia, Kuala Lumpur, Malaysia

Abstract

The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.

DOI

10.22237/jmasm/1604188920

Recommended Citation

Mahmood, E. A., Midi, H., & Hussin, A. G. (2019). The comparison between maximum weighted and trimmed likelihood estimator of the simple circular regression model. Journal of Modern Applied Statistical Methods, 18(2), eP2689. doi: 10.22237/jmasm/1604188920