Rank-Based Estimation for Linear Models

Rank-based (R) estimation and inference for linear models. Estimation is for general scores and a library of commonly used score functions is included.

Rfit: Rank-based estimation for linear models

  • Rfit may be installed from
    • CRAN e.g. install.packages('Rfit')
    • github e.g. install_github('kloke/Rfit')
  • Rfit no longer requires the package quantreg The inital fit is now based on least squares to avoid additional dependencies. One may still use quantreg to obtain the inital fit which will ensure the robustnesses of the result.

CRAN releases are about once a year while github updates are more frequent.


Rank-based (R) estimation for statistical models is a robust nonparametric alternative to classical estimation procedures such as least squares. R methods have been developed for models ranging from linear models, to linear mixed models, to timeseries, to nonlinear models. Advantages of these R methods over traditional methods such as maximum-likelihood or least squares is that they require fewer assumptions, are robust to gross outliers, and are highly efficient at a wide range of distributions. The R package, Rfit, was developed to widely disseminate these methods as the software uses standard linear model syntax and includes commonly used functions for inference and diagnostic procedures.


Reference manual

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0.24.2 by John Kloke, 2 years ago

Browse source code at https://github.com/cran/Rfit

Authors: John Kloke , Joseph McKean

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on methods

Suggests testthat

Imported by NSM3, chipPCR, mvctm.

Depended on by DBfit, Rbent.

See at CRAN