search for: uvec

Hello, I'm running into a very strange problem: > xrange <- c(-2.5,2.5) > xdim <- 100 > mobility <- 0.1 > slope <- 1.16 > urange <- slope*xrange > udim <- max(slope*xdim,5) > du <- (urange[2]-urange[1])/udim > uvec <- urange[1]+(1:udim-0.5)*du > # type dependent weight function > ckern <- array(0,dim=c(udim,udim)) > diag(ckern) = wfun(uvec,slope,mobility) Error in `diag<-`(`*tmp*`, value = c(0.992300064325398, 0.990746129315703, : replacement diagonal has wrong le...

Dear GeoR-er, If I use the variog function in the latest release of geoR, the first lag is always ignored. For instance, if you read in geodata, calculates the variogram using the variog function and give in a uvec like uvec=seq(0,max,by=2.44), it only starts giving results from distance=4.88 and ignores 2.44! This wasn't the case in former versions of geoR. Is this done on purpose? Why? Tnx for your help, Dave Nys K.U.Leuven Laboratory for Forest, Nature and Landscape Research Vital De Costerstraat 102...

Hi all, I tried to produce some kriged surfaces with geoR (latest version). The size of the grid should be around 900 x 650 cells (what I find is not a very big grid), and the number of points is around 2500. The command krige.conv stopped after arround 5 min saying it can not allocate a vector with around 1.5 billion units. Sounds reasonable. Is there a workaround? How would I partition the

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Please see the code below. When I try to run the variogram - vg.deft<-variog(rd,uvec=10) I keep getting this error- variog: computing omnidirectional variogram Error in vector("double", length) : vector size specified is too large Also, when I try to define distance-based neighborhood - nb.tr=dist.neighbors(tr.locs,2) I get this error - Error in vector("double"...

...; design locations <- cbind(wl1$X,wl1$Y) extent <- max(dist(locations)) max.dist <- extent/2 data1 <- cbind(wl1$X,wl1$Y,wl1$PSI*1000) geodata1 <- as.geodata(data1, coords.col = 1:2, data.col = 3) # Calculate the sample variogram vario_var1 <- variog(geodata1, uvec = nlags, trend = trend, option = "bin", estimator.type = "modulus", max.dist = max.dist, pairs.min = 10., direction = "omnidirectional", messages = TRUE) # Fit a model variofit_var1 <-...

...s [1] 14.5665 $output.type [1] "bin" $max.dist [1] 10000 $estimator.type [1] "classical" $n.data [1] 10000 $lambda [1] 1 $trend [1] "cte" $pairs.min [1] 2 $nugget.tolerance [1] 1e-12 $direction [1] "omnidirectional" $tolerance [1] "none" $uvec [1] 250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 5750 6250 6750 7250 [16] 7750 8250 8750 9250 9750 $call variog(coords = coords, data = data$slp, breaks = breaks, option = "bin") attr(,"class") [1] "variogram" ************************* Sean Parks Eco...

All, I am new to using R and know some basics. I wish to use kriging in R to do the following: given data Y =f(X1,X2,X3,.....,Xn) --1000+ irregular measured data set. I would like to be able to get a single value y given sinle input set (x1,x2,x3,...xn) A google search on this takes me lierally to the same example on involving analysis with soil sampling and I cannot figure out how to