The combined dynamically weighted modified maximum likelihood estimators of the location and scale parameters

ABSTRACT

In this study, two new types of estimators of the location and scale parameters are proposed having high efficiency and robustness; the dynamically weighted modified maximum likelihood (DWMML) and the combined dynamically weighted modified maximum likelihood (CDWMML) estimators. Three pairs of the DWMML and two pairs of the CDWMML estimators of the location and scale parameters are produced, namely, the DWMML1, the DWMML2 and the DWMML3, and the CDWMML1 and the CDWMML2 estimators, respectively. Based on the simulation results, the DWMML1 estimators of the location and scale parameters are almost fully efficient (under normality) and robust at the same time. The DWMML3 estimators are asymptotically fully efficient and more robust than the M-estimators. The DWMML2 estimators are a compromise between efficiency and robustness. The CDWMML1 and CDWMML2 estimators are jointly very efficient and robust. Particularly, the CDWMML1 and CDWMML2 estimators of the scale parameter are superior compared to the other estimators of the scale parameter.

KEYWORDS:

• Combined dynamically weighted modified maximum likelihood
• dynamically weighted modified maximum likelihood
• least squares
• M-estimators
• modified maximum likelihood
• robustness

Acknowledgement

I am very grateful to the Editor for his very positive attitude and to the Associate Editor and the reviewer for very helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the author.

ORCID

Hakan Savaş Sazak http://orcid.org/0000-0001-6123-1214