Re: [R] D(dnorm...)?

From: <>
Date: Thu 26 Jan 2006 - 18:56:50 EST

While symbolic computation is handy, I actually think a more pressing addition to R is some kind of automatic differentiation facility, particularly 'reverse mode' AD, which can be spectacular. There are free tools available for it as well, though I don't know how well developed they are. See:

I admit this is not quite the same thing, but for statistical computations this is, in my experience, the key thing you need. (Well, for frequentist estimation at any rate...)

There are commercial systems that use this idea already, of course. Two that I know of are 'ADMB' (and its associated 'ADMB-RE' for random effects) estimation and of course the 'S-NUOPT' module for another system not unlike R.

ADMB is, frankly, difficult to use but it performs so well and so quickly once you get it going nothing else seems to come close to it. I has become almost a de-facto standard at the higher end of the fishery stock assessment game, for example, where they are always fitting huge, highly complex and very non-linear models.

Bill V.

-----Original Message-----
From: Berwin A Turlach [] On Behalf Of Berwin A Turlach
Sent: Thursday, 26 January 2006 4:50 PM
To: Spencer Graves
Cc: Venables, Bill (CMIS, Cleveland);;; Subject: Re: [R] D(dnorm...)?

G'day Spencer,

>>>>> "SG" == Spencer Graves <> writes:

    SG> I'm not qualified to make this suggestion since I'm incapable     SG> of turning it into reality, [...] This statement applies to me too, nevertheless I would like to point out the following GPL library:

I am wondering since some time how hard it would be to incorporate that library into R and let it provide symbolic differentiation capabilities for R.


        Berwin mailing list PLEASE do read the posting guide! Received on Thu Jan 26 19:03:56 2006

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