similar to: How to make an orderly matrix from geostatistical data?

Hi all, I use kriging to interpolate the precipitation from stations, but the map of this results show lots of stripes. (please see the attachment)I think there's something wrong with the setting of the dimension of this matrix, however, I have no idea how to know or test to see if this setting is correct or not.I've tried to switch the latitude and longitude, but still got the same

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

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

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

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) >

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.

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

Hi If you read the description of "varcov.spatial" you'll see that it is used to *predict* a covariance matrix, based on the parameters of the covariance function. So you don't need the oebserved data, you need parameters for the covariance function. Regards EJ On Thu, 2003-04-17 at 05:43, Yan Yu wrote: > THanks for the suggestion. > I have a Q when trying to use it..

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 I have two geostatistical models from geoR. An ordinary kriging model with AIC=-148.6 and a universal kriging model with AIC=-156.7, there are 345 data points. The improvement shown by the AIC by adding a trend component to the model seems quite small given the number of data points, is there a test to see if the improvement to the model fit is significant? Thanks David

Dear all, Sorry for such basic question, but. when R "says": library(Rcitrus) Loading required package: geoR Loading required package: sp ------------------------------------------------------------- Analysis of geostatistical data For an Introduction to geoR go to http://www.est.ufpr.br/geoR geoR version 1.6-8 (built on 2006/06/29) is now loaded

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

Juan Zwolinski wrote: > > 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) > >

Hi, I read somewhere that when carrying out geostatistical analysis in R you should not use latitude and longitude...can anyone expand on this a little for me, and what would be the best coordinate system to use? I have my data in a geographic coordinate system, WGS84, decimal degrees....is this the wrong format for such analyses? I have also converted my data in the UTM projection and so have

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

Hello, I'm interested in doing Bayesian kriging using R. I see that the package geoR has a function that will allow one to do this (krige.bayes). However, my data are not in the form of points, but rather they are blocks that represent spatial averages (i.e., the number of fishing hooks per month in a given lat x long square). I am therefore interested in treating the data as

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

Dear all, I wonder about what could actually be possible with the function "contour": 1/ - the definition of contour lines is most often meaningless when the contours are drawn in areas where no real data points exist. It can however happen that irregular distributions lead to more or less irregular clouds of data points. Interpolations (eg: loess regression, GLM, etc...) are however

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

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.