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An R package containing tools for linear fitting of complex variables. Includes ordinary least squares and M-estimator robust functions.

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QuantumOfMoose/complexlm

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Software and datasets to support 'Modern Applied Statistics with S', 
fourth edition, by W. N. Venables and B. D. Ripley.
Springer, 2002.

From the text (pp. 464):

    These datasets and software are provided in good faith, but none of
    the authors, publishers nor distributors warrant their accuracy
    nor can be held responsible for the consequences of their use.

This file is intended to clarify ownership and copyright: where
possible individual files also carry brief copyright notices. 


Copyrights
==========

File MASS/R/profiles.R copyright (C) 1996 D. M. Bates and W. N. Venables.
                       port to R by B. D. Ripley copyright (C) 1998
                       corrections copyright (C) 2000,3,6 B. D. Ripley

Our understanding is that the dataset files MASS/data/*.rda are not copyright.

All other files are copyright W. N. Venables and B. D. Ripley. Those
parts which were distributed with the first edition are also copyright
(C) 1994 Springer-Verlag New York Inc, with all rights assigned to
W. N. Venables and B. D. Ripley.


Licence
=======

    This is free software; you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation; either version 2 or 3 of the License
    (at your option).

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

Files share/licenses/GPL-2 and share/licenses/GPL-3 in the R
(source or binary) distribution are copies of versions 2 and 3
of the 'GNU General Public License'.
These can also be viewed at https://www.r-project.org/Licenses/

[email protected]
[email protected]

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An R package containing tools for linear fitting of complex variables. Includes ordinary least squares and M-estimator robust functions.

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