[R] geoR - help for bayesian modelling
Monica Palaseanu-Lovejoy
monica.palaseanu-lovejoy at stud.man.ac.uk
Mon Apr 19 14:03:11 CEST 2004
Hi,
I am trying to do a bayesian prediction for soil pollution data above
a certain threshold, using geoR.
Everything is working fine until i am doing the krig.bayes ( I am
using as a guide the geoR tutorial from the web page
http://www.est.ufpr.br/geoR/geoRdoc/geoRintro.html#starting). I
tried to do the prediction on a grid 67 by 113 cells and my
computer is freezing to death. At larger numbers of cells it tells me
after a while that it reaches the max. memory of 511 Mb. My
computer has only 512 Mb of RAM. What RAM capacity should i
look for to do a 150 x 250 cell grid??? (I tried the modelling on a 1
Gb RAM computer and it didn't work either). I am interested to do a
modelling where my resolution is 5 m x 5 m (150 x 250 grid cell).
If i want to do the prediction on my initial data locations (well,
actually the prediction points are shifted 1 m in X and respectively
Y direction, so the raw data coordinates don't coincide with the
prediction coordinates) i am getting the following error using the
command:
zn.bayes <- krige.bayes(zn.gdata, loc = xy, model =
model.control(cov.model = "exponential", lambda = 0), prior =
prior.control(phi.prior ="exponential", phi = 89.1894),
output=output.control(n.predictive=2, mean.var = TRUE, quantile =
c(0.025,0.25, 0.5, 0.75, 0.975), threshold = c(300)))
Error in cond.sim(env.loc = base.env, env.iter = iter.env,
loc.coincide = get("loc.coincide", :
chol: matrix not pos def, diag[13]= -1.279220e-018
I will really appreciate any suggestion you may have.
Thank you so much,
Monica
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