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Rfit: Rank-based Estimation for Linear Models

John D. Kloke,J. McKean

Published 2012 in The R Journal

ABSTRACT

In the nineteen seventies, Jureckova 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 of influential cases. We have developed an R package, Rfit, for computing of these robust procedures. In this paper we highlight the main features of the package. The package uses standard linear model syntax and includes many of the main inference and diagnostic functions.

PUBLICATION RECORD

  • Publication year

    2012

  • Venue

    The R Journal

  • Publication date

    Unknown publication date

  • Fields of study

    Mathematics, Computer Science

  • Identifiers
    DOI 10.32614/RJ-2012-014
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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