[Rd] bug (PR#13570)

[Prof Brian Ripley]

On Thu, 5 Mar 2009, Benjamin Tyner wrote:

> Hi
>
> Nice to hear from you Ryan. I also do not have the capability to debug on 
> windows; however, there is a chance that the behavior you are seeing is 
> caused by the following bug noted in my thesis (available on ProQuest; email 
> me if you don't have access):
>
> "When lambda = 0 there are no local slopes to aid the blending algorithm, yet 
> the
> interpolator would still assume they were available, and thus use arbitrary 
> values
> from memory. This had implications for both fit and tr[L] computation. In the
> updated code these are set equal to zero which seems the best automatic rule 
> when
> lambda = 0." [lambda refers to degree]
>
> I submitted a bug fix to Eric Grosse, the maintainer of the netlib routines; 
> the fixed lines of fortran are identified in the comments at (just search for 
> my email address):
>
> http://www.netlib.org/a/loess
>
> These fixes would be relatively simple to incorporate into R's version of 
> loessf.f

The fixes from dloess even more simply, since R's code is based on 
dloess.  Thank you for the suggestion.

Given how tricky this is to reproduce, I went back to my example under 
valgrind.  If I use the latest dloess code, it crashes, but by 
selectively importing some of the differences I can get it to work.

So it looks as if we are on the road to a solution, but something in 
the current version (not necessarily in these changes) is incompatible 
with the current R code and I need to dig further (not for a few 
days).

> Alternatively, a quick check would be for someone to compile the source 
> package at https://centauri.stat.purdue.edu:98/loess/loess_0.4-1.tar.gz and 
> test it on windows. Though this package incorporates this and a few other 
> fixes, please be aware that it the routines are converted to C and thus there 
> is a slight performance hit compared to the fortran.
>
> Hope this helps,
> Ben

[...]

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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