## Rfit: Rank-based
estimation for linear models

### Installation

- 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.

### Background

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. Rfit uses standard linear model syntax and
includes commonly used functions for inference and diagnostic
procedures. Wilcoxon scores, the default, are robust and highly efficent
relative to the least squares estimator when the errors are normally
distributed.