Combining some biased estimation methods with least trimmed squares regression and its application Combinación de algunos métodos de estimación sesgados con regression de mínimos cuadrados recortados y su aplicación

KAN KILINÇ B., ALPU Ö.

Revista Colombiana de Estadistica, vol.38, no.2, pp.485-502, 2015 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 2
  • Publication Date: 2015
  • Doi Number: 10.15446/rce.v38n2.51675
  • Journal Name: Revista Colombiana de Estadistica
  • Journal Indexes: Scopus
  • Page Numbers: pp.485-502
  • Keywords: Biased Estimator, Least Trimmed Squares, Robust Estimation
  • Anadolu University Affiliated: Yes

Abstract

© 2015 Revista Colombiana de Estadística. All rights reserved.In the case of multicollinearity and outliers in regression analysis, the researchers are encouraged to deal with two problems simultaneously. Biased methods based on robust estimators are useful for estimating the regression coefficients for such cases. In this study we examine some robust biased estimators on the datasets with outliers in x direction and outliers in both x and y direction from literature by means of the R package ltsbase. Instead of a complete data analysis, robust biased estimators are evaluated using capabilities and features of this package.