similar to: default value for cutoff in gstat variogram()

Hi, I am new in R and trying to implement an algorithm which makes ordinary kriging by using gstat library and the predict method. I use the predict method as following: First, I create an object g: g <- gstat(id="tec", formula=TEC ~ 1, data=data) ## Create gstat object called g And then I use this object in the predict. p <- predict.gstat(g, model=mod, newdata=predGrid,

Dear All, Is there anybody has the experience in using variogram(gstat) ? Please kindly give me some hints about the results. I used variogram() to build a semivariogram plot as: tr.var=variogram(Incr~1,loc=~X+Y,data=TRI2TU,width=5) then fir the variogram to get the parameters as: v.fit = fit.variogram(tr.var,vgm(0.5,"Exp",300,1)) v.fit model psill range 1 Nug 1.484879

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

Dear Members, I am trying to fit a variogram model using fit.variogram function from the gstat package. The figure showing my experimental variogram can be seen here: https://i.stack.imgur.com/UZXw4.png My code line for this operation is: > c2.vgm.fit<-fit.variogram(c2.vgm.exp,vgm(nugget=0, psill=400,model="Exp",range =40000),fit.method = 7) The system throws following error

Dear all can you help me? i have this problem: i have a dataset in a text file in a matrix of 3 columns: x, y, z where x and y are the coordinates and Z are the mesurements. How can i do a variogram with R?

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

I have what R seems to consider a very large dataset, a 12MB text file of lat,long,and height values, 130,000 rows to be exact. Here's what I get: Thomas Colson North Carolina State University Department of Forestry and Environmental Resources (919) 673 8023 tom_colson at ncsu.edu Calendar: www4.ncsu.edu/~tpcolson

Thanks to Edzer and Roger, I can now plot with increased font sizes. However, jpeg still does not reproduce these, nor does it show up in high quality. What I would like to do is produce some highresolution jpegs. Any help would be appreciated Thanx Herry R2.4 on Mandriva 10.2 linux. Dr Alexander Herr Spatial and statistical analyst CSIRO, Sustainable Ecosystems Davies Laboratory, University

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.

hello I need basic explanation of variogram and how to use in R. I will appreciate if you supply them. regards Ahmet Temiz ______________________________________ XamimeLT - installed on mailserver for domain @deprem.gov.tr Queries to: postmaster at deprem.gov.tr ______________________________________ The views and opinions expressed in this e-mail message are ...{{dropped}}

Dear Users, I use Sgeostat to calculate co variogram (function est.variogram with two variables). If i inverse the 2 variables in the functions, the co variogram change! Normaly it is symmetric, isn't it? Someone could me explain why, or give me an idea to calculate co variogram in a easy way... Thanks in advance Laurent ps : sorry for my english Laurent William Dubroca Centre de

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 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 list, I am having troubles increasing the fontize when plotting a variogram{gstat} and its model (vgm) with plot and using jpeg(). Also the resolution in the jpeg call does not work. I am using R2.4 on Mandriva 10.2 linux. I can change fontsize with cex.axis in a normal plot, so I presume it has to do with plotting the variogram model. Any help on how to increase the font size and

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

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

Hi all, >str(df) `data.frame': 31837 obs. of 3 variables: $ x : num 410683 410700 410720 410740 410324 ... $ y : num 43136 43126 43123 43125 42709 ... $ wz: num -101.1 -94.9 -93.3 -94.5 30.8 ... >library(gstat) >g<-gstat(id="rv",form=wz~1,loc=~x+y,data=df,model=mat,nmax=500,set=list(average=1)) >str(g) List of 3 $ data :List of 1 ..$ rv:List of 10 ..

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?