similar to: bug in geoR (?)

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

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 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?

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

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

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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,

Mac OS 10.3.5, R 2.0.0 latest version of geoR I have an incomplete 5 x 20 spatial array of samples (60 out of 100 possible locations) for which I would like to calculate directional variograms using variog4(). Unfortunately, I can't get it to return all 4 directions. It returns variograms for 45, 90, and 135 degrees, omitting 0 degrees (pi/4, pi/2, 3pi/4, omitting 0). If I specify 0

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, 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 have defined a function to compute the value of a beta distribution of the second kind (the existing beta distribution of th stats package is the beta distribution of the first kind). It works perfectly for a single value, but I want to apply it to a vector of 22 000 values. I can use a loop for the calculation of each value but it runs very very slowly. So, what can I change ? Hers's the

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,

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 --

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 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 R users, The parameters xaxs and yaxs (function par, package graphics) seem not to work with the function hist (package graphics), even when the parameters xlim and ylim are defined. Is there any way to make yaxs="i" and xaxs="i" work properly with the function hist, mainly to produce histograms that "touch" the horizontal axis? The R documentation and the R

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 want to insert a small figure into a bigger plot. I saw people are doing this all the time, but I just could not figure out how to do it in R. Thanks for your help! Jinfeng Zhang

Hi all! Does anyone knows if it exists a "symbolic math" package in R, that allows to compute derivatives, integrals, etc.? Does exist a freeware version of Maple? Cheers, Marco [[alternative HTML version deleted]]

I am attempting to develop a multiple regression model using selected model variables that should all be treated as numeric (mostly real) values. However, R considers one specific variable "mass" automatically to be of class "factor", probably because "mass" consists of integer values that are repeated. I now want to force R to treat "mass" as a numeric