similar to: question about krige code in R

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

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, 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

Hi ALL, Can you please help me on how to determine the prediction error for ordinary kriging?Below are all the commands i used to generate the OK plot: rsa2 <- readShapeSpatial("residentialsa", CRS("+proj=tmerc +lat_0=39.66666666666666 +lon_0=-8.131906111111112 +k=1 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs")) x2 <- readShapeSpatial("ptna2",

Greetings all, Ran into a strange problem with the krige function from geoR. The problem that I am having is that while the krige function seems to work well, the resulting predicted values are all NAs. Given the size of the datasets I am working with can't attach it, but I can provide snippets of the datasets. > casedata station year month day obs mpe bias type

Hello, I'm interested in doing Bayesian kriging using R. I see that the package geoR has a function that will allow one to do this (krige.bayes). However, my data are not in the form of points, but rather they are blocks that represent spatial averages (i.e., the number of fishing hooks per month in a given lat x long square). I am therefore interested in treating the data as

Hi! Im new to R and I need to interpolate a shapefile using kriging. I've been able to plot/read the shapefile using the package maptools or rgdal. I've searched the internet for sample codes but most of the kriging codes that I've found done in R is done using txtfiles or CSVs.  An example could be of great help. Thanks. [[alternative HTML version deleted]]

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

Hello All! I like to do some indicator kriging with R. So far I used geoR for simple and ordinary kriging. Does anybody know which package I should use? Thanks for your help! Sascha! -- Jetzt dabei sein: http://www.shortview.de/wasistshortview.php?mc=sv_ext_mf at gmx

Hi, I am very new to R and I am trying to write KML files. I am running R-2.13.1 and I have the following packages: - AKIMA - RGDAL - RSAGA - SP I was trying to run the simple example that I found at the following web page: http://spatial-analyst.net/wiki/index.php?title=Export_maps_to_GE The lines that I can run are: data(meuse.grid)

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

Thank you Sarah and Mike for your explanations. My final objective is to produce maps (png image or any kind of extension I can import in LaTeX) where rainfall data are interpolated, using the Inverse Distance method or Kriging. My input file (pointfile.csv in the reported example) reports the station code, lat and long of the meteorological station and the rainfall value (which might be the

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

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 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 everybody: I just generate different maps of interpolation with different methods but with the same package -(gstat, i used the krige command). And now for evaluate the best method i want to compare the predict values versus experimental, but i don't know how do it. Could anybody tell me how should do it?. Thanks in advance. -- ######################################## Antoni Vi??dez

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

Fwiw the engine behind geom_raster needs explicit observation-per-row form for input (with no structural normalization), so conversion to points is perfectly proper here, albeit confusing in context. (It's closer to what graphics devices actually use ultimately, but the expansion is laid out very early in ggplot2 because there's no standard for intermediate forms.) Cheers, Mike On Wed,

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) >

Hi list, Well, this time I’ve a doubt with mapping generation. I was already able to read and plot shapefiles, plot point on this map. All this without any problems, but now I want to do something that I think, only Golden Software Surfer is capable of. I would like to plot a kriging result on the existing map (map script below). Well I looked for on the net, but I was not able to be sure of