Bibliographie complète
Estimates of the Regression Coefficient Based on Kendall's Tau
Type de ressource
Auteur/contributeur
- Sen, Pranab Kumar (Auteur)
Titre
Estimates of the Regression Coefficient Based on Kendall's Tau
Résumé
Abstract The least squares estimator of a regression coefficient β is vulnerable to gross errors and the associated confidence interval is, in addition, sensitive to non-normality of the parent distribution. In this paper, a simple and robust (point as well as interval) estimator of β based on Kendall's [6] rank correlation tau is studied. The point estimator is the median of the set of slopes (Yj - Yi )/(tj-ti ) joining pairs of points with ti ≠ ti , and is unbiased. The confidence interval is also determined by two order statistics of this set of slopes. Various properties of these estimators are studied and compared with those of the least squares and some other nonparametric estimators.
Publication
Journal of the American Statistical Association
Volume
63
Numéro
324
Pages
1379-1389
Date
1968-12-01
Extra
DOI: 10.1080/01621459.1968.10480934
MAG ID: 2018764772
Référence
Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934
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