From pgilbert@bank-banque-canada.ca  Mon Nov 30 19:24:08 1998
From: pgilbert@bank-banque-canada.ca (Paul Gilbert)
Date: Mon, 30 Nov 1998 14:24:08 -0500
Subject: [R] R functionality
References: <199811301829.SAA07623@toucan.stats.ox.ac.uk>
Message-ID: <98Nov30.143327est.13479@mailgate.bank-banque-canada.ca>

PG>Problems which require lots of looping and cannot be re-coded as
vector/matrix
PG> operations are theoretically possible but practically infeasible in S,
unless
PG> they  are coded in C or Fortran and called from S. These problems seem to
run
PG> fine in R.

BR>Some but not all...

TL> As R is much faster on _some_ code ...

BR>Agreed, but as my anecdote shows, much slower on other code.
BR>`Your mileage may differ.'

Well, for the record, my milage is that Splus 3.3 is generally about twice as
fast as R with Solaris 2.6 on a Sparc Ultra10 doing my standard test set of
problems. These tests call Fortran for the main loop of ARMA and state space
time series models and use Splus "For" loops (which are a real pain to debug)
for monte-carlo simulations and "For" loops calling the "For" loops (which are a
super pain to debug) for evaluating estimation techniques. In R, I use "for"
loops.

However, I've been experimenting with some other time series models which I have
not (and cannot easily) code in fortran. In R it is true that I have to tweak
the nsize and vsize. Too much will cause paging. But I can run the monte-carlo
simulations and also evaluate estimation techniques in a reasonable time. In
Splus it seems these would take years to run. Apart from setting the nsize and
vsize too large and causing paging I have not run into the situation that R is
orders of magnitude slower than Splus.

Paul Gilbert

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[R] R functionality
Paul Gilbert