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