[R] Nonlinear statistical modeling -- a comparison of R and AD Model Builder

[Mike Prager]

dave fournier <otter at otter-rsch.com> wrote:

> I  think that many R users understimate the numerical challenges
> that some of the typical nonlinear statistical model used in different
> fields present. R may not be a suitable platform for development for
> such models.
> 
> Around 10 years ago John Schnute, Laura Richards, and Norm Olsen
> with Canadian federal fisheries undertook an investigation
> comparing various statistical modeling packages for a simple
> age-structured statistical model of the type commonly used in
> fisheries. [...] It is possible
> to produce a working model with the present day version of R so that
> R can now be directly compared with AD Model Builder for this type of model.
> 
> The results are that AD Model builder is roughly 1000 times faster than
> R for this problem. ADMB takes about 2 seconds to converge while
> R takes over 90 minutes.

Our group's experiences reflect, at least qualitatively, what
Dave says above.  We use R for analyzing results from models
written in his AD Model Builder, and a couple of years ago, we
started programming one of our models directly in R.  We quickly
abandoned that idea because of lengthy execution time under R.
That is not a judgement of either piece of software.  R and ADMB
are designed for different types of task, and it seems to me
that they complement each other well.

That experience was in part the genesis of our X2R software (now
at CRAN -- pardon the plug), which saves results from ADMB
models into a format that R can read as a list.  We feel that
now we have the best of both worlds -- fast execution with ADMB,
followed by the programming ease and excellent graphics of R for
analysis of results and projections under numerous scenarios.

-- 
Mike Prager, NOAA, Beaufort, NC
* Opinions expressed are personal and not represented otherwise.
* Any use of tradenames does not constitute a NOAA endorsement.