Nonlinear Regression Modelling using Robust Methods

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.)


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install.packages("nlr")

0.1-1 by Hossein Riazoshams, a year ago


http://www.riazoshams.com/nlr/


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


Authors: Hossein Riazoshams


Documentation:   PDF Manual  


GPL-2 license


Imports MASS, nlme, robcor, TSA, tseries, stats, GA, quantreg

Depends on methods


See at CRAN