One-step M-estimators: Jones and Faddy's skewed t-distribution

ACITAŞ Ş., KASAP P., ŞENOĞLU B., ARSLAN O.

JOURNAL OF APPLIED STATISTICS, vol.40, no.7, pp.1545-1560, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 40 Issue: 7
  • Publication Date: 2013
  • Doi Number: 10.1080/02664763.2013.788620
  • Journal Name: JOURNAL OF APPLIED STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1545-1560
  • Keywords: one-step M-estimator, modified likelihood, regression, robustness, efficiency, PARTIALLY ADAPTIVE ESTIMATION, MAXIMUM-LIKELIHOOD, ROBUST ESTIMATION, REGRESSION, ASYMPTOTICS, PARAMETERS, LOCATION
  • Anadolu University Affiliated: Yes

Abstract

One-step M (OSM)-estimator needs some initial/preliminary estimates at the beginning of the calculation process. In this study, we propose to use new initial estimates for the calculation of the OSM-estimator. We consider simple location and simple linear regression models when the distribution of the error terms is Jones and Faddy's skewed t. Monte-Carlo simulation study shows that the OSM estimator(s) based on the proposed initial estimates is/are more efficient than the OSM estimator(s) based on the traditional initial estimates especially for the skewed cases. We also analyze some real data sets taken from the literature at the end of the paper.