similar to: 2/3d interpolation from a regular grid to another regular grid

Hello Trying to develop variograms and kriged surfaces from a point file. Here is what I've done so far. library(gstat) # also loads library(sp) library(lattice) soilpts$x <- soilpts$UTM_X soilpts$y <- soilpts$UTM_Y soil.dat <- subset(soilpts, select=c(x, y, Area, BulkDensity, LOI, TP, TN, TC, Total_Mg)) dim(soil.dat) [1] 1292 7 coordinates(soil.dat) <- ~ x+y

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

Hi, all, Have anyone used kringing included in R? How is it? Does it handle anisotropy data well? How does it compare with Kriging in Arc/Info? or other geostatistics software customized to do kriging or other geostatistics functions? I tried Easykriging, a geostatistics tool developed for Matlab. It has very nice GUI, but it does not provide library which i can call in my programs. so it is

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

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])

Hi All, I am a PhD student in forestry science and I am working with LiDAR data set (huge data set). I am a brand-new in R and geostatistic (SORRY, my background it?s in forestry) but I wish improve my skill for improve myself. I wish to develop a methodology to processing a large data-set of points (typical in LiDAR) but there is a problem with memory. I had created a subsample data-base but

Hi list, Well, this time I’ve a doubt with mapping generation. I was already able to read and plot shapefiles, plot point on this map. All this without any problems, but now I want to do something that I think, only Golden Software Surfer is capable of. I would like to plot a kriging result on the existing map (map script below). Well I looked for on the net, but I was not able to be sure of

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

Hello again, There is any package which does Z aware (real 3D) interpolations? It can be any method (IDW, kriging or spline) but it should take into consideration not only x and y coordinates for interpolation, but also z coordinate. I looked into different packages but it seems i didn't find the right one. The ultimate goal is to import the output into a GIS (Geographical Information

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Mike J Smith > Sent: 09 June 2005 09:58 > To: r-help at stat.math.ethz.ch > Subject: [R] krig.image help > > > Hi > > I have recently been experimenting with the use of kriging, primarily > through Goldensoftware's Surfer.

Hello to everybody ! I don't have a question directly connected with R, but it takes starting point from the use of the R function Krig for kriging interpolation and from the idea of making a different implemetation of the function for my purposes. Doas anyone know where can I find free C or C++ codes of kriging ? As always, thanks a lot in advance, Paola.

> both "_ "and "<-" are assignment operators well, I've changed it in my script, but the result is the same. > what do you get if you call > > in.polygon(grid2.point$x,grid2.point$y,polygon$x,polygon$y) That's it ! In fact all my points in grid2.point where xy inverted. And I had no points in polygon. It was really a stupid mistake. Thanks for all !

Hi ! Sorry for my ignorance. I have two questions: 1) which is in R the function to make a covariogram of spatial data ? 2) does anyone know if there exist the possibility in R of performing kriging with an arbitrary covariance function ? If I have well understood the Krig procedure offers only three possibilities (expcov, gauscov and sphercov) that are the common models for stationary and

R Experts, I'm looking for some help with the geoR package. I'm trying to krig some data without using a global neighborhood. I would like to set my moving neighborhood to a distance, say 100 meters, where I know my data is spatially correlated. I have tried the ksline function, but that only allows my moving neighborhood to be set to a number of data points. But, since my data

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

Hi R-people: Working in geoRglm, it shows me, according to AIC criterion, that the non-spacial model describes the process in a better way. It's the first time that I'm facing up to. These are my results: OP2003Seppos.AICnonsp-OP2003Seppos.AICsp #[1] -4 (OP2003Seppos.lf0.p<-exp(OP2003Seppos.lf0$beta)/(1+exp(OP2003Seppos.lf0$beta))) #P non spatial #[1] 0.9717596

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

Dear R community, I'm having hard time to understand the kde function in "ks" package. Let me use a 3-dimensional kernel smooth example to explain my question using the elevation data in geoR. ### here is what I did ### library(ks) require(geoR) data(elevation) elev.df <- data.frame(x = elevation$coords[,"x"], y = elevation$coords[,"y"], z = elevation$data)

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

Hi, I have a 4 column file (long/lat/elev/variable) and I tried to fit the values of my variable to the XYZ space using Tps and I keep getting the following message: Warning messages: 1: GCV search gives a minumum at the endpoints of the grid search in: Krig.find.gcvmin(info, lambda.grid, gcv.grid$GCV, Krig.fgcv, 2: GCV search gives a minumum at the endpoints of the grid search in: