similar to: new gstat version

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

Hi, please help!! I've been trying to fit variogram models using the REML method in the gstat package. Every time the Windows GUI crashes. For example library(gstat) data(meuse) x <- variogram(zinc ~ 1, ~x + y, meuse) v <- vgm(140000, "Sph", 800, nug = 10000) plot(x, model = fit.variogram(x, model = v, fit.method=5)) Other fit methods are non problematic (eg. fit.method=7

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'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

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

Hi ALL, With the pakage gstat How can one create a grid of points as in the meuse.grid example, from measuring sites as in the Meuse example Thanks in advance! Alain PONSERO Conservateur Réserve Naturelle de la Baie de Saint-Brieuc site de l'Etoile 22120 HILLION tel/fax : 02.96.32.31.40 <mailto:aponsero@cabri22.com> aponsero@cabri22.com

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

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

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

Hola, # Hacemos el KED. Ver función "krige()": KED.rad <- krige( formula=pluvPcp~layer, # covariable -> radar locations=lluvia.rad.pluv.spdf, newdata=radarGrid, # podría ser cualquier objeto Spatial model=v.fit, # modelo de semivariograma. maxdist=Inf

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?

Sale plano sí. Ya se que sin tener los datos y el código es un poco difícil, pero es que mis datos ocupan mucho, es imposible. Seguiré mirando por internet. Muchas gracias Rubén. Un saludo, > To: r-help-es en r-project.org > From: rubenfcasal en gmail.com > Date: Thu, 6 Aug 2015 14:21:47 +0200 > Subject: Re: [R-es] Duda interpolación (package ' gstat ') > > Hola

Hi, I need help! I am trying to iterate an iterative process to do cross vadation and store the results each time. I have a Spatial data.frame, called Tmese > str(Tmese) Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 14 obs. of 17 variables: .. ..$ ID : int [1:14] 73 68 49 62 51 79 69 77 57 53 ... .. ..$

Dear All, I run following code to estimate the blocks using cokriging ( my data set has more than 50,000 data points). All the things run finely but Once I run the predict.gstat function it gave the error message - "memory.c", line 58: can't allocate memory in function m_get(). I run this code on LINUX sever but result is same. Would any one please be able to give a solution for

Hi All, I am a PhD student in forestry science and I am working with LiDAR data set (huge data set). I am a brand-new in R and geostatistic (SORRY, my background it?s in forestry) but I wish improve my skill for improve myself. I wish to develop a methodology to processing a large data-set of points (typical in LiDAR) but there is a problem with memory. I had created a subsample data-base but

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, 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,

Hi, I'm using R 2.5.1 and gstat 0.9-39 library and I'm working with the jura data set provided by gstat library. I tried to plot a graph of metal concentrations (let's say Cd) with the command spplot, but I realized that the default lags are equally distributed between Min and Max. I did: library(gstat) data(jura) jura.pred.xy <- jura.pred names(jura.pred.xy)[1:2] <-