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Rfit: Rank-based Estimation for Linear Models
2012
The R Journal
In the nineteen seventies, Jurečková and Jaeckel proposed rank estimation for linear models. Since that time, several authors have developed inference and diagnostic methods for these estimators. These rank-based estimators and their associated inference are highly efficient and are robust to outliers in response space. The methods include estimation of standard errors, tests of general linear hypotheses, confidence intervals, diagnostic procedures including studentized residuals, and measures
doi:10.32614/rj-2012-014
fatcat:aftpei3icrfk7ep6ijyeo333ey