Hi Nick, Very interesting problem. At first thought, I imagined that you just want to simulate noise ;)
In the geoR package (http://leg.ufpr.br/geoR/) there is a function to simulate Gaussian Random Fields (uses actually RandomFields package) using various models e.g.: > library(geoR) ------------------------------------------------------------- Analysis of geostatistical data For an Introduction to geoR go to http://www.leg.ufpr.br/geoR geoR version 1.6-27 (built on 2009-10-15) is now loaded ------------------------------------------------------------- > s <- grf(100, grid="reg", cov.pars=c(2, 0.2), cov.model="mat", kappa=1.5) grf: generating grid 10 * 10 with 100 points grf: process with 1 covariance structure(s) grf: nugget effect is: tausq= 0 grf: covariance model 1 is: matern(sigmasq=2, phi=0.2, kappa = 1.5) grf: decomposition algorithm used is: cholesky grf: End of simulation procedure. Number of realizations: 1 > image(s, col=gray(seq(1, 0.2, l=21))) > hist(s$data) # normal distribution You can also simulate a regular point sample with the same spatial structure on top of that using either Poisson, Bernoulli or binomial models. For example, to simulate a Poisson model, you could use: # define your own model, e.g. poisson: > lambda <- exp(0.5 +s$data) > y <- rpois(length(s$data), lambda=lambda) > points(y) > text(s$coords, label=y, pos=3, offset=0.3) > hist(y) For a uniform model, I would then use the Empirical Cumulative Distribution Function (ECDF): # uniform distribution: > y.cdf <- ecdf(s$data) > y <- y.cdf(s$data) > image(s, col=gray(seq(1, 0.2, l=21))) > points(y) > text(s$coords, label=y, pos=3, offset=0.3) > hist(y) This would then have the same spatial auto-correlation structure and 'perfectly' uniform distribution (I might also be wrong - I do not like that a simulated variable has a perfect histogram). I am sure that other mathematicians have maybe better ideas. HTH T. Hengl http://home.medewerker.uva.nl/t.hengl/ > -----Original Message----- > From: r-sig-geo-boun...@stat.math.ethz.ch > [mailto:r-sig-geo-boun...@stat.math.ethz.ch] On Behalf > Of Nick Hamm > Sent: Tuesday, November 17, 2009 10:06 AM > To: r-sig-geo@stat.math.ethz.ch; ai-geost...@jrc.it > Subject: [R-sig-Geo] Unconditional simulation > > Dear all > > I want to simulate a spatially-correlated random field which follows a > uniform rather than than Gaussian distribution. Does anybody know a > straight-forward way to do this? > > Nick > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo