similar to: points geodata {geoR}

I've enconuntered this problem with the last cran version of geoR: > library(geoR) > day <- rep(1:2, each=5) > coords <- matrix(rep(runif(10),2), 10, 2) > data <- rnorm(10) > data[1] <- NA > as.geodata(cbind(coords, data, day), realisations=4) as.geodata: 1 points removed due to NA in the data Errore in as.geodata(cbind(coords, data, day), realisations = 4) :

Hi, I'm a new R user. My goal is to do a variogram using geoR. I started by trying to do the example in the geoR Illustrative Session using my own data. I am able to read in my Ascii data using: D <- matrix(scan("file.dat", n=530*3), 530,3, byrow=TRUE). Then I use: as.geodata(D, coords.col=1:2, data.col=3) to make the object D geodata. I check the descriptive statistics,

ComRades: I am geeting the error message Error in ldots[[which(MET)]] : attempt to select less than one element when I try to fit the geostatistical model with the likfit() function of geoR. I have tried with old data for which likfit() successfully maximised the likelihood in previous versions of geoR, and yet the current version fails. I have tried in Windows Vista and Windows XP (I haven't

Sorry, this is probably quite an easy question, but I'm new to R and couldn't find the answer anywhere. I'm using geoR and geoRglm, but can't figure out how to get a border in my geodata object. Does this need to be defined when I'm importing my data, or afterwards, and how do I go about doing this? Thanks -- View this message in context:

Hi, Im using geoR and I'm trying to do some predictions, based on an external trend. I'm having some problems specifying my model.control, specifically how do I define my model, and also the source of the covariate data at the prediction locations? I am assuming that the covariate data at the prediction locations should be imported to a geodata object along with the prediction location

Hi everyone !   I'm am trying to fit a kriging model to a set of data. When I just run the "likfit" command I can obtain the results. However when I try to pass additional arguements to the optimization function "optim" I get errors. That is I want to obtain the hessian matrix so matrix (hessian=TRUE).   Heres a little example( 1-D). Can anyone shed some light?  Where am I

Mzabalazo Ngwenya wrote: > Hi everyone ! > > I'm am trying to fit a kriging model to a set of data. When I just run > the "likfit" command I can obtain the results. However when I try to > pass additional arguements to the optimization function "optim" I get > errors. That is I want to obtain the hessian matrix so matrix > (hessian=TRUE). >

Hi, I am trying to do a bayesian prediction for soil pollution data above a certain threshold, using geoR. Everything is working fine until i am doing the krig.bayes. I tried to do the prediction on a grid 67 by 113 cells and my computer is freezing to death. At larger numbers of cells it tells me after a while that it reaches the max. memory of 511 Mb. My computer has only 512 Mb of RAM.

Hi, everybody! i created a imagem by kriging using geoR package. I imported points from GRASS("zn", after converted to geodata "zn_geo"), the border "zn_border" and a raster mask. Then i interpolated the points by kriging and created a raster image. Now, i need export this image back to GRASS to use it in the module r.mapcalc. I can't do it. I tried use

Hi all, I have to draw a map of microorganisms repartition in a sample. I use the "image" function of geoR package to build the map but there are three problems: 1) the legend is Horizontal (with or without vert.leg=TRUE) 2) I want to plot the position of organisms and level curves of density on the map but I don't find the script to insert these data on the map. 3)the grey range

Hello All! I calculate a variogram using the function variog (package geoR) afterwards I use variofit to fit a spherical model (see code below). Now I just changed the units of the variable (in this case MPa to kPa just a factor of 1000). If I do so, I get a different fit and therefore different ranges etc. Why? The semi-variance is of course 6 orders of magnitude higher but the values

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?

Hello, I'm new to this list. Sorry if my question or parts of it already came up before. For my research in geostatistics, I am working with large sets of data in R (basically large matrices containing discrete x and y coordinates and a value for a certain parameter). These sets are obtained by kriging. The operation I'd like to perform is smoothen the output data set. I want to do it by

Dear, we have a problem with geoR. We try to read an ASCII table (x,y,z) with 40000 lines. With read.geodata we get the error: Error in vector("double", length) : cannot allocate vector of length 799980000 We can read the file without any problem with read.table, but trying to convert it to the geodata class gets the same error. Any help/tips would be appreciated. Kris, Dave --

I'm using R for Mac OSX version 1.14 (2129) and the geoR package version 1.6-5 (the current version in the R repository). I'm running R in OS 10.4.6 on a Mac G4 iBook (933MHz, 640 MB DDR SDRAM). I searched the R archive and did not find a posting on this issue. I want to use the variog and variog4 functions of geoR to characterize the pattern of spatial autocorrelation of tree

Dear Aaron, I am really a tool user and not a tool maker (actually an ecologist doing some biostatistics)... so, I take the liberty of sending a copy of this e-mail to the r-help list where capable computer persons and true statisticians may provide more relevant information and also to Paulo Ribeiro and Peter Diggle, the authors of geoR.. I really feel that your huge matrix cannot be

I am having difficulty getting the trend.spatial function in geoR to work properly. After creating a trend.spatial object with a covariate, I try to add the command into my likfit() function as follows: trend1.trend.spatial <- trend.spatial("1st", trend1.geodata) trend1.spatial.EC0.1.reml <- likfit(spatial.geodata, trend1.trend.spatial, ini.cov.pars = spatial.EC0.1.eyefit,

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

Hello, I am attempting to get the standard deviation in multiple distance bins in my spatial data. It appears as though the 'variog' command in the geoR package will do the trick, as one of the outputs from 'variog' is 'variog$sd', which, according to the manual, is the "standard deviation of the values in each bin". However, when I run this command, the

Dear R list, I've just installed R and then followed the instructions to install the package "geoR" from within R by using the following line of code: install.packages("geoR", contriburl = "http://www.est.ufpr.br/geoR/windows") This installed okay under the folder C:\documents and settings\ ... But when I follow the instructions in the illustrative session