[RsR] Fwd: smart updates and rolling windows

[Gabor Grothendieck]

Yes,   Jarek Tuszynski, the author of caTools, posted a performance comparison
of different methods for rolling calculations using R code and zoo used
that to provide the fastest method in his list for each case.  By using C
as in caTools you can get it even faster.

On 9/30/07, Bradford Cross <bradford.n.cross using gmail.com> wrote:
>
>
> On 9/29/07, Gabor Grothendieck <ggrothendieck using gmail.com> wrote:
> > On 9/29/07, Bradford Cross <bradford.n.cross using gmail.com> wrote:
> >
> > > I found a couple simple summary statistics implemented like this in the
> zoo
> > > package.  I have also found implementations for smart updates in some
> other
> > > languages (apache commons math, and BOOST accumulators) but these only
> > > supports accumulated calculations, not rolling calculations.
> >
> > I am not sure whether your last sentence was intended to apply to zoo
> > but zoo has several functions for rolling calculations: rollapply,
> rollmax,
> > rollmean, rollmedian .  The rollaply is quite general since you
> > supply the function.  The caTools package has some high performance
> > functions: runmean, runmin, runmax, runquantile.
> >
>
> Thanks for pointing out caTools.  Rollapply is great for the general case -
> but it uses brute force calculation.  That is why there are the special
> rollmean, rollmedian because the underlying calculation algorithms still
> need to be optimized to get any performance gain.  I suppose a good pattern
> is to use rollapply to test things out, and if particular statistics prove
> especially useful, then optimize the calculation algorithm and add it to a
> specialized library. :-)
>