Non-Linear Robust package is developed to handle the problem of outliers in nonlinear regression, using robust statistics. It covers classic methods in nonlinear regression as well. It has facilities to fit models in the case of auto correlated and heterogeneous variance cases, while it include tools to detecting outliers in nonlinear regression. (Riazoshams H, Midi H, and Ghilagaber G, (2018, ISBN:978-1-118-73806-1). Robust Nonlinear Regression, with Application using R, Joh Wiley and Sons.)
| Version: | 0.1-1 |
| Depends: | R (≥ 3.0.0), methods |
| Imports: | MASS, nlme, robcor, TSA, tseries, stats, GA, quantreg |
| Published: | 2018-03-21 |
| Author: | Hossein Riazoshams |
| Maintainer: | Hossein Riazoshams <riazihosein at gmail.com> |
| License: | GPL-2 |
| URL: | http://www.riazoshams.com/nlr/ |
| NeedsCompilation: | no |
| CRAN checks: | nlr results |
| Reference manual: | nlr.pdf |
| Package source: | nlr_0.1-1.tar.gz |
| Windows binaries: | r-devel: nlr_0.1-1.zip, r-release: nlr_0.1-1.zip, r-oldrel: nlr_0.1-1.zip |
| OS X binaries: | r-release: nlr_0.1-1.tgz, r-oldrel: nlr_0.1-1.tgz |
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