similar to: How to make Ordinary Kriging using gstat predict?

I wonder what is the default value for the argument 'cutoff' when not specified in the variogram.formula function of gstat. Computing variogram envelops within gstat, I am comparing the results obtained with variog in geoR and variogram in gstat, and it took me a while before understanding that the cutoff default value is not the maximum distance. Can Edzer tell us about it? All the

HI, I wonder does anyone have experience with doing sequential gaussian simulation with krige() function in gstat? I find it VERY slow compared to use krige() to achieve kriging function itself.. I wonder why, is that because it has to model the variogram, and do the kriging separately for each point to be simulated? so it would be N times slower to achieve the simulation than the kriging if

ear ALL, The last part of my thesis analysis is the cross validation. Right now I am having difficulty using the cross validation of gstat. Below are my commands with the tsport_ace as the variable: nfold <- 3 part <- sample(1:nfold, 69, replace = TRUE) sel <- (part != 1) m.model <- x2[sel, ] m.valid <- x2[-sel, ] t<- fit.variogram(v,vgm(0.0437, "Exp", 26, 0)) cv69

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

Hi, I am a student at the University of Twente ( ITC). I am using the R packages for my data analysis, but for the last few weeks now , I have been getting the error message when trying to work on variograms or krigging. Error : .onLoad failed in loadNamespace() for 'gstat', details: call: fun(...) error: .Random.seed is not an integer vector but of type 'list' Error:

The majority of the functionality present in the gstat stand-alone program (http://www.gstat.org/) is now available as a package/library for the S language (R, S-Plus), again called gstat. The package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. Gstat was started 10 years ago and was released under the GPL in 1996; the

The majority of the functionality present in the gstat stand-alone program (http://www.gstat.org/) is now available as a package/library for the S language (R, S-Plus), again called gstat. The package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. Gstat was started 10 years ago and was released under the GPL in 1996; the

Hi all-- I'm new to R, statistics and programming, so sorry if this is a really basic question! I have plotted a directional variogram, and I want to a. overlay the omni-directional line over each directional panel b. display the directional variograms in a single panel with a legend that associated each line to each degree measurement. The line I'm using is

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) > >

Dear all, I am aiming to calculate variograms using variogram() from gstat. The problem is that some of my data-sets are very large (> 400000 points). Running the command takes some hours of time and does not give any error-message. Nevertheless the result seem not to be appropriate - the first few bins are ok (up to a distance of about 300) but then it gains lags which are much larger than

I have a question to everybody. After log10 transfprmation, I have done ordinary kriging in gstat in R? I need to back trnasform the prediction values to orgiginal scale. How do I do this in gstat in R? Thanks Zia -- Zia Uddin Ahmed 915 Brad Field Hall Department of Crop and Soil Cornell University Ithaca NY 14850 USA

R Users: ...been working with the sp and gstat packages for the past couple of days in an effort to analyze a set of ~ 200 soil samples collected from various eastings, northings, and depths and containing a wide range of measured hydrocarbon concentrations. Thus far, I've managed to import the data, log-transform the concentrations, assign coordinates, generate and fit a variogram model and

I uploaded gstat 0.9-12 to CRAN, which has a few important changes: 1. Cokriging cross validation Cokriging cross validation is now possible with the function gstat.cv: you simply pass a multivariable gstat object, and cross validation is done for the first variable in the object. Optionally, secondary variable records at locations coinciding with the validation locations are removed. 2. Class

I uploaded gstat 0.9-12 to CRAN, which has a few important changes: 1. Cokriging cross validation Cokriging cross validation is now possible with the function gstat.cv: you simply pass a multivariable gstat object, and cross validation is done for the first variable in the object. Optionally, secondary variable records at locations coinciding with the validation locations are removed. 2. Class

Hello, # I am able to install.packages("gstat") #but when I try to upload I get an error message library(gstat) #Error in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]) : # there is no package called ‘intervals’ #In addition: Warning message: #package ‘gstat’ was built under R version 3.0.2 #Error: package or namespace load failed for ‘gstat’ what do

Hello, I'm using the gstat package within R for an automated procedure that uses ordinary kriging. I can see that there is a logical ("singular") atrtibute of some adjusted model semivariograms: .- attr(*, "singular")= logi TRUE I cannot find documentation about the exact meaning and the implications of this attribute, and I dont know anything about the inner calculations

Hi everybody, I have a longitude vector and a latitude one. Associated to these coordinates, i have a matrix with some data at some coordinates but not all. Lon <- seq(136.025,144.975,0.05) Lat <- rev(seq(-66.975,-65.525,0.05)) dim(z) <- c(Lon,Lat) And i have tried to apply to these data a kriging function. But first i need to reshape these 3 variables to have a dataframe

Hi there, I have a problem using gstat when attempting to fit a regression-kriging model to my data. I have successfully carried out a stepwise regression on my data and I have the model residuals. However when I try to apply a variogram to the residuals I get the following error message; *>>>Error in grid.newpage() : * * VECTOR_ELT() can only be applied to a 'list', not a

Soon on CRAN a new version of package gstat will emerge, which has a few minor changes and possible incompatibilities w.r.t. the previous version(s). The new gstat (0.9-23) now: + depends on sp, and uses internally with Spatial* classes from sp if data are provided in the old-fashoned way (as data.frame) + has a vignette to get you started with the classes in sp + defines krige as a generic;