similar to: Variogram with Gstat

Hi all-- I'm new to R, statistics and programming, so sorry if this is a really basic question! I have plotted a directional variogram, and I want to a. overlay the omni-directional line over each directional panel b. display the directional variograms in a single panel with a legend that associated each line to each degree measurement. The line I'm using is

Hello, I'm using the gstat package within R for an automated procedure that uses ordinary kriging. I can see that there is a logical ("singular") atrtibute of some adjusted model semivariograms: .- attr(*, "singular")= logi TRUE I cannot find documentation about the exact meaning and the implications of this attribute, and I dont know anything about the inner calculations

Hi, I would know how to plot two variograms on a same graph. I can plot one by one but I would draw both on the same one. Is it possible? Do i need any special package? Thanks! Cordialement Damien Landais

Hi, please help!! I've been trying to fit variogram models using the REML method in the gstat package. Every time the Windows GUI crashes. For example library(gstat) data(meuse) x <- variogram(zinc ~ 1, ~x + y, meuse) v <- vgm(140000, "Sph", 800, nug = 10000) plot(x, model = fit.variogram(x, model = v, fit.method=5)) Other fit methods are non problematic (eg. fit.method=7

Hi; I cannot find in the R html documentation a way to evaluate cross-correlation in 2D data sets. I would like to evaluate cross-correlation in a series of moving windows between two maps. i,e, specify several windows inside the complete 2D spatial matrixes and for each one ofthese windows evaluate the 2D cross-correlation (commonly conducted in the spectral domain). Thanks in advance and best

Hello. I'm pretty much new to R and I'm trying to produce some figures. It seems to me, that R has some asynchronous way of plotting figures. When I run this code: #constructs the semivariogram of SC1929 vgm1 <- variogram(SC1929~1,~U+V,puerto.map$att.data) # trying to make new plot dev.set(which=dev.next()) plot(vgm1) title(main="Semivariogram",font.main=4)

hello, i do the following in order to get an persp-plot x<-c(2,2,2,2,2,2,3,3,3,3) y<-c(41,41,83,83,124,166,208,208,208,208) z<-c(90366,90366,92240,92240,92240,96473,100995,100995,100995,100995) x<-data$x y<-data$y z<-matrix(data$z,length(y),length(x)) persp(x,y,z, col="gray") but i always get the error message increasing 'x' and 'y' values expected,

Dear list, I am having troubles increasing the fontize when plotting a variogram{gstat} and its model (vgm) with plot and using jpeg(). Also the resolution in the jpeg call does not work. I am using R2.4 on Mandriva 10.2 linux. I can change fontsize with cex.axis in a normal plot, so I presume it has to do with plotting the variogram model. Any help on how to increase the font size and

I wonder what is the default value for the argument 'cutoff' when not specified in the variogram.formula function of gstat. Computing variogram envelops within gstat, I am comparing the results obtained with variog in geoR and variogram in gstat, and it took me a while before understanding that the cutoff default value is not the maximum distance. Can Edzer tell us about it? All the

Dear Members, I am trying to fit a variogram model using fit.variogram function from the gstat package. The figure showing my experimental variogram can be seen here: https://i.stack.imgur.com/UZXw4.png My code line for this operation is: > c2.vgm.fit<-fit.variogram(c2.vgm.exp,vgm(nugget=0, psill=400,model="Exp",range =40000),fit.method = 7) The system throws following error

Dear All, I run following code to estimate the blocks using cokriging ( my data set has more than 50,000 data points). All the things run finely but Once I run the predict.gstat function it gave the error message - "memory.c", line 58: can't allocate memory in function m_get(). I run this code on LINUX sever but result is same. Would any one please be able to give a solution for

Hi, I'm using R 2.5.1 and gstat 0.9-39 library and I'm working with the jura data set provided by gstat library. I tried to plot a graph of metal concentrations (let's say Cd) with the command spplot, but I realized that the default lags are equally distributed between Min and Max. I did: library(gstat) data(jura) jura.pred.xy <- jura.pred names(jura.pred.xy)[1:2] <-

Dear all, I have a database x,y,value imported in R with read.table: dati<- read.table("dati.dat") value is a categorical data (land use) and i want to plot in the same colour the same land use. It is possible with R. Thanks a lot

The following came up when Roger Bivand and I discussed R's name spaces and overlap in packages, in the bus to the field trip during StatGIS, last Tuesday: If two packages create the same class, say "variogram", and both are loaded, then using a method for an object of class "variogram" cannot discriminate between them and will call the method in the package loaded last.

Hi ALL, With the pakage gstat How can one create a grid of points as in the meuse.grid example, from measuring sites as in the Meuse example Thanks in advance! Alain PONSERO Conservateur Réserve Naturelle de la Baie de Saint-Brieuc site de l'Etoile 22120 HILLION tel/fax : 02.96.32.31.40 <mailto:aponsero@cabri22.com> aponsero@cabri22.com

Dear All, Is there anybody has the experience in using variogram(gstat) ? Please kindly give me some hints about the results. I used variogram() to build a semivariogram plot as: tr.var=variogram(Incr~1,loc=~X+Y,data=TRI2TU,width=5) then fir the variogram to get the parameters as: v.fit = fit.variogram(tr.var,vgm(0.5,"Exp",300,1)) v.fit model psill range 1 Nug 1.484879

I uploaded gstat 0.9-12 to CRAN, which has a few important changes: 1. Cokriging cross validation Cokriging cross validation is now possible with the function gstat.cv: you simply pass a multivariable gstat object, and cross validation is done for the first variable in the object. Optionally, secondary variable records at locations coinciding with the validation locations are removed. 2. Class

I uploaded gstat 0.9-12 to CRAN, which has a few important changes: 1. Cokriging cross validation Cokriging cross validation is now possible with the function gstat.cv: you simply pass a multivariable gstat object, and cross validation is done for the first variable in the object. Optionally, secondary variable records at locations coinciding with the validation locations are removed. 2. Class

Hello, I'm french and I have some difficulties in carry out the semiones under R with an aim to carry out an interpolation by krigeage. My goal is to obtain a chart of the distribution of precipitations/temperatures in Europe starting from 73 different stations (and, of course, distributed irregularly on the chart, where use of the krigeage). Here, I carried out this to test to obtain

Hola, # Hacemos el KED. Ver función "krige()": KED.rad <- krige( formula=pluvPcp~layer, # covariable -> radar locations=lluvia.rad.pluv.spdf, newdata=radarGrid, # podría ser cualquier objeto Spatial model=v.fit, # modelo de semivariograma. maxdist=Inf