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.)


Reference manual

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0.1-1 by Hossein Riazoshams, a year ago

Browse source code at

Authors: Hossein Riazoshams

Documentation:   PDF Manual  

GPL-2 license

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

Depends on methods

See at CRAN