similar to: Some problems with X11

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

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

Hello, I am a graduate student of University of Florida. I am trying to run a process variation model and I am facing the following error. ------------------------------------------------------------- Analysis of geostatistical data For an Introduction to geoR go to http://www.leg.ufpr.br/geoR geoR version 1.6-27 (built on 2009-10-15) is now loaded

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

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.

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 am struggling to fit a non-linear trend using the likfit function in geoR. Specifically I want a sigmoidal function, something like SSfpl in the nls package to fit the trend. But it seems trend.spatial in geoR only works with lm or glm type models. Any ideas how I can specify the model to calculate the kriging parameters using REML, including the parameters of a sigmoidal trend function

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?

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

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.

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)

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 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

Full_Name: Mikhail Bocharov Version: 2.2.1 OS: Linux Submission from: (NULL) (62.148.130.28) Cyrillic UTF8 letters are imaged incorrectly Sorry, but English is not my native language My operating system is Gentoo-linux. Now i want get the gparhics with russian title for example: plot(1:20, type='l', main='&#1059;&#1090;&#1077;&#1095;&#1082;&#1072;')

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

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of dwfu > Sent: 11 June 2005 13:59 > To: r-help at stat.math.ethz.ch > Subject: Re: [R] R-help Digest, Vol 28, Issue 11 > > > Dear all, > I'm new using R and in (geo)statistics. I have a problem with solving > my homework questions.

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,

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

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

Dear R users: I want to model mosquito count data based on landcover attributes and meteorological variables using a Poisson GLSM in the geoRglm package. I have monthly mosquito counts over more than 20 years with repeated observations from individual trap sites over time. I have used as.geodata() to successfully read my dataset into the geodata format utilized by geoR and geoRglm,