similar to: still have problem with krige and border option [end]

Dear all, I would like to estimate rainfall with the krige function. First, I produce a polygon of my region of interest (where poly_test.txt is a x,y suite of points defining a polygon, obtained with the grass v.out.ascii command) : user>border_limite<-read.table("/home/lionel/rwork/poly_test.txt",header=FALSE) user>polygone<-list(x=border_limite[,1],y=border_limite[,2])

Dear all, I'm new on R and this mailing list. We work on spatial rainfall estimation with R and Grass. We have a problem with the krige function from the sgeostat package. We would like to limit the estimated area with a polygon limit. I use a 50 points polygon to describe my work area. The krige function work quiet well without limit. But if I use this option I have the following error

Dear all, I have a problem with the readline editor of R since it doesn't work. Setting ./configure --with-readline does not the fix the problem. Does anyone have an idea how to fix this? Many thanks in advance! Peter Schlattmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html

Tried to post this last night, but it doesn't seem to have appeared. Using R 2.0.1 on Windows XP + SP2. I am traveling, away from my usual references. I'm trying to make a 4-dimensional plot: a levelplot with overlaid contours, with different response variables represented by (1) colors on the levelplot and (2) the contour lines. First try was filled.contour + contour but the key

Hello, This is what I am trying to do: I wrote a little function that takes addresses (coordinates) as input, and returns the road distance between every two points using Google Maps. Catch is, there are 2000 addresses, so I have to get around 2x10^6 addresses. On my first go, this is what I did: ######################################### getRoadDist = function(X,complete=F){ # X must be a

Hello R users, I have numerical data sampled on two grids, each one shifted by 0.5 from the other. For example: grid1 = expand.grid(x=0:3, y=0.5:2.5) grid2 = expand.grid(x=0.5:2.5, y=0:3) gridFinal = expand.grid(x=0.5:2.5, y=0.5:2.5) plot(gridFinal, xlim=c(0,3), ylim=c(0,3), col="black", pch=19) points(grid1, xlim=c(0,3), ylim=c(0,3), col="red", pch=19) points(grid2,

Dear all, When a conventional kriging and then a contour plot is limited with a polygon (as possible with krige.conv and contour.kriging), the polygon border is displayed in black by default. > kc<-krige.conv(CZdata,loc=pred.grid,borders=czpoly,krige=krige.control(obj.m=ls)) > plot(CZcoord,xlab="x",ylab="y",type="n",asp=1) >

Dear expeRts, The order in which the variables vary in expand.grid() is often unintuitive. I would like to suggest a 'method' slot for expand.grid() which requires only very little changes (100% backward compatible) and which allows one to control this order. Please find attached diffs against R-devel. Cheers, Marius ### ./src/library/base/R/expand.grid.R

Hi R-users, I'm attempting to fit a number of mixed models, all with the same structure, across a spatial grid with data points collected at various time points within each grid cell. I'm trying to use a 'for' loop to try the model fit on each grid cell. In some cells lme does not converge, giving me the error: Error message: In lme.formula(logarea ~ year + summ_d, data =

Moved the node administration elements to a separate submenu. Created a new network administration menu. * users can define a network * users can create a network * users can destroy a network * users can undefine a network * users can list existing networks, including details Each new command is also available as a separate command line executable as well. Signed-off-by: Darryl L. Pierce

A majority of my data makes a kriged map perfectly using an exponential model for the semivariogram to fit my data and then going through the commands variofit() to define the model and then krige.conv() to use the model to predict values in a grid. But?one set of my data appears to be linearly correlated for the first 5000 meters and not correlated beyond that. I have been having problems

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HI, I wonder does anyone have experience with doing sequential gaussian simulation with krige() function in gstat? I find it VERY slow compared to use krige() to achieve kriging function itself.. I wonder why, is that because it has to model the variogram, and do the kriging separately for each point to be simulated? so it would be N times slower to achieve the simulation than the kriging if

Hello, I used glsm.mcmc and likfit.glsm to create model. Now I want to predict at different locations, but I can't get glsm.krige to work. I keep getting the error that trend.d and trend.l must have similar specifications. I have tried numerous ways to include the covariates in the glsm.krige model, and I keep getting the same error message. The bolded part is the part that doesn't work.

Hi, I'm using the function krige.conv from package geoR but I'm getting a warning that I do not understand: Warning messages: 1: NaNs produced in: sqrt(variance) 2: NaNs produced in: sqrt(variance) I'm performimg an ordinary kriging with a log transform (lambda=0). Does anyone knows where this comes from ? Thanks and regards EJ

I?m trying to make an estimation of sea-depth for 2000 animal locations using 2 million depth soundings. The result was: Cannot allocate vector of size 20351 Kb I've tried to overcome this problem by making the following adaptations. -Increased the max-mem-size to 1.5Gb (Thanks to Thomas Lumley for his help) -Use a max.dist (10km) for the function Krige -Run the Krige computation for each

Greetings all, Ran into a strange problem with the krige function from geoR. The problem that I am having is that while the krige function seems to work well, the resulting predicted values are all NAs. Given the size of the datasets I am working with can't attach it, but I can provide snippets of the datasets. > casedata station year month day obs mpe bias type

Hi everybody ! I'm new to R (used to Matlab ...) and I 'd like to use R at home ...

Hi everybody ! I'm new to R (used to Matlab ...) and I 'd like to use R at home ... I've installed it from RPM package (R-base-1.2.1-2.i386.rpm) on a linux RedHat 7.0, succesfully ....however but I've got problems with running the demos, it says : "/usr/lib/R/bin/R.bin : error while loading shared libraries : /usr/lib/R/bin/R.bin : symbol __sysconf, version GLIBC_2.2

I'm performing ordinary and simple kriging from a set of non-negative values: >krige.control.sk<-krige.control(type.krige="sk",obj.model=my.variogram.model,beta=my.variogram.model$beta) >sk<-krige.conv(cadiz.geo,data=amostragem.cadiz$dia1.std,locations=as.matrix(cadiz.polygrid[,c(1,2)]),krige=krige.control.sk) krige.conv: model with constant mean krige.conv: Kriging