[R] Nonlinear regression

[Bill.Venables at csiro.au]

There is no question that SAS is a monumental piece of software that has
served the statistical community well for a very long time.  No question
at all in my mind of that.  There is an ugly side to it though.
Possibly unconsciously, it tries to make its culture and customs a kind
of standad for the statistical profession, and some of those customs and
cultural features are, to put it as mildly as possible, rather
unhelpful.

As I said quite a few years ago now, 'SAS seems to be to statistical
computing what Microsoft is to personal computing'.  Or at least it
tries to be, sadly.

W.  



-----Original Message-----
From: Spencer Graves [mailto:spencer.graves at pdf.com] 
Sent: Wednesday, 21 May 2008 10:03 AM
To: Venables, Bill (CMIS, Cleveland)
Cc: LXu at hnrg.com; r-help at r-project.org
Subject: Re: [R] Nonlinear regression

      Let's not be so hard on SAS.  I thought it was marvelous when I 
first used it over 30 years ago. 

      Spencer Graves

Bill.Venables at csiro.au wrote:
> ?nls
>
> (I always knew SAS *is* a DUD, but never that it has a DUD too...) 
>
>
> Bill Venables
> CSIRO Laboratories
> PO Box 120, Cleveland, 4163
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>
> -----Original Message-----
> From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org]
> On Behalf Of LXu at hnrg.com
> Sent: Wednesday, 21 May 2008 9:23 AM
> To: r-help at r-project.org
> Subject: [R] Nonlinear regression
>
> Could someone help me on the following:
> SAS has DUD (Does not Use Derivatives) for nonlinear regression.
>
> Does "R" has a similar capability?
>
> I am not good at derivatives and may get my derivative wrong before 
> feeding it to a nonlinear regression procedure.
>
> Any help would be much appreciated. 
>
> Liu
> Hancock Forest Management NZ
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