From hankin.robin at gmail.com  Thu Apr 14 08:07:32 2011
From: hankin.robin at gmail.com (robin hankin)
Date: Thu, 14 Apr 2011 18:07:32 +1200
Subject: [Rd] Using GSL Routines
In-Reply-To: <BANLkTimacZbmyyqsL6052W_1Y2Y_rob3ZQ@mail.gmail.com>
References: <BANLkTimacZbmyyqsL6052W_1Y2Y_rob3ZQ@mail.gmail.com>
Message-ID: <BANLkTi=WXkQf8YUbt8XGpLXf0SZFr0vPKw@mail.gmail.com>

Hi

the gsl R package includes many wrappers which you may find useful,
but if you write new ones please let me know and I'll include them
in a future release.

best wishes

Robin

On Thu, Apr 14, 2011 at 5:49 PM, Mohit Dayal <ken.sensei at gmail.com> wrote:
> Dear R-programmers,
>
> I am trying out certain methods in R, and the statistics require me to
> calculate n-(sample size) dimensional equations. They are not really very
> hard to solve - my home-brew implentation of Newton-Raphson in R succeeds
> most of time with simulated data. (Note that I am assured of a unique
> solution by theory). Problem comes in with real data, for which I should
> really implement a good line search (convergence issues). Being lazy, i
> would like to link to the GSL routines which are of course faster and more
> reliable.
>
> My question is should i use the C - GSL routines or the Python ones in
> NumPy? My major concern is the portability of the code i write: really dont
> want users to have to install a bunch of software just to use my package.
> (Im looking at Windows here)
>
> Alternatively, should i just hack out the code (fsolve) and put it in my
> package?
>
> Thanks for the advice,
> Mohit Dayal
> Applied Statistics & Computing Lab
> ISB
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>



-- 
Robin Hankin
Uncertainty Analyst
hankin.robin at gmail.com



[Rd] Using GSL Routines
robin hankin