gstat now uses Lapack

gstat 1.1-0, now on CRAN, no longer comes with its own functions for
matrix factorization and solving systems of equations [1], but now
directly uses Lapack (dpotrf and dtrsm) through R's own lapack interface
and R_ext/Lapack.h header files.

For global kriging at one location from 10,000 observations, as in

library(sp)
library(gstat)
set.seed(1331)
n = 10000
pts = SpatialPoints(cbind(x = runif(n), y = runif(n)))
pts$z = runif(n)
k <- krige(z~1, pts, pts[1,], vgm(1, "Exp", 1))

I see a speed increase from 120 (gstat 1.0-26) to 46 seconds; using
openblas on a 4 core laptop brings this down to 15 seconds - I expect
sth similar with MKL/RevoR.

For local kriging on large data sets with smaller neighborhoods and many
locations, I wouldn't expect large improvements; for global kriging of
large data sets to many prediction locations, krige0 may be faster when
you use openblas or MKL - as long as things fit in memory.

I'd be happy to hear experiences (positive and negative), or otherwise
reactions or questions.

[1] it formerly used meschach,
http://homepage.math.uiowa.edu/~dstewart/meschach/