Marcelo,

although I would like to wait for Paulo's comments, here are
my two brief remarks:

1. if your data set is large, say over 3000 observations, and you
want to use kriging, you'd better use kriging in a local
neighbourhood. I think geoR does not provide this, another
R package that does so is package gstat. The quote you
mention ignores this common practice.
2. if your data are in lat/lon, you may want to project them
first -- to my knowledge all geostats software assumes data
in a plane (or 3D data, but not on a sphere): one unit in x direction
should equal one unit in y direction. In lat/lon, it generally doesn't.

Best regards,
--
Edzer

Marcelo Alexandre Bruno wrote:

Dear list-members

I try to run geoR for generate interpolation maps.
My data is: x(longitud, decimal degree),y(latitud,
decimal degree),z(Sa, acoustic parameter, limits range
is 0 to 1000000, extremely skewed, represent
backscatering echoes signals of fish schools). The
dataset is 3007 nautic miles of sampling!

The analysis is run according to steps of Dr. Paulo
Justiano's homepage
http://www.est.ufpr.br/~paulojus/geoR/geoRdoc/geoRintro.html#starting
.
When kriging run, consume all memory of system, (R.bin with only geoR consumes 86.8mb!! in Athlon
xp1.6GHz, Linux redhat 9.0, 250mb + swapp 541mb).
Is there something wrong (possible newbie question)
or its possible vectorizing computations to
reduce memory consume?



"The necessary reliance on a n by n matrix, where n represents the number of observations, greatly impedes traditional spatial statistics from handling larger sample sizes." published from: Pace, R. Kelley, and Ronald Barry, "Fast CARs," Journal of Statistical Computation and Simulation, Volume 59, Number 2, 1997, p. 123-147.

This is the case??
(Apologies for my long msg.)
Thanks for all.

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Yahoo! Mail - o melhor webmail do Brasil
http://mail.yahoo.com.br

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