similar to: spatial markov chain methods

I need you help with this problem, I have a data-frame like this: BHID=c(43,43,43,43,44,44,44,44,44) FROM=c(50.9,46.7,44.2,43.1,52.3,51.9,49.3,46.2,42.38) TO=c(46.7,44.2,43.1,40.9,51.9,49.3,46.2,42.38,36.3) AR=c(45,46,0.0,38.45,50.05,22.9,0,25,9) DF<-data.frame(BHID,FROM,TO,VALUE) #add the length DF$LENGTH=DF$FROM-DF$TO where: + BHID: is the borehole

Dear list members, I have a large dataset with point data. Each data point has X, Y, number of species present and values for one single explanatory variable. Each point was generated from a polygon grid shapefile and they are at equal distances. I conducted GLS analyses introducing variance structures and correlation structures to improve the model. I plotted variograms before and after adding

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

Hi; I cannot find in the R html documentation a way to evaluate cross-correlation in 2D data sets. I would like to evaluate cross-correlation in a series of moving windows between two maps. i,e, specify several windows inside the complete 2D spatial matrixes and for each one ofthese windows evaluate the 2D cross-correlation (commonly conducted in the spectral domain). Thanks in advance and best

Hi all, This is more a help on ideas that on actuall R code. Those of you which are geologist or work with boreholes woudl understand that i would like to achieve. I'll tr to explain as good as I can...so here it goes.. I have around 1000 geomechanical (geological) borehole logs in a database. The logs contain staial info, lithology and some laboratory data. My initial goal is

Dear R users, I am putting together reading and resources lists for spatial statistics and spatial econometrics and am looking for some pointers from more experienced practitioners. In particular, I find two "camps" in spatial modelling, and am wondering which approach is better suitied to which situation. The first camp is along the lines of Venables and Ripley's Chapter 14

Hello R list, I need to compute empirical variograms using data from a large geographic area (~10^6 km2). Although I could not find a specific reference, I assume that both geoR and gstat calculate distances among data points assuming points are on a flat surface (using the Pythagorean Theorem). Because the location of my data is large and located near the pole, assuming that latitude and

Hi, I would know how to plot two variograms on a same graph. I can plot one by one but I would draw both on the same one. Is it possible? Do i need any special package? Thanks! Cordialement Damien Landais

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, I want to automatically fit variograms to a large number of different sample data sets, and call the funtion "likfit" (in package geoR) from within a for-loop. "likfit" does again call "optim". After ssuccessfully fitting variograms to some of the data sets, the procedure crashes and I get the error message: Error in optim(par = ini, fn = negloglik.GRF,

Hello everyone! I am using GRASS with spgrass6 for my work. I will be using variograms in the process of landsat image classification. I am quite ok with GRASS but am finding R really tough. I understand that spgrass6 is a link between GRASS and R which can read and write raster/vector layers. Out of really many packages in R, for generating variograms out of landsat images which packages of R

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

Hello, Could someone tell me whether the spatial statistics module of Splus is worth the rather high price, or whether one could (with reasonable effort) carry out the same things using R and some of its contributed packages. Although we do have Splus (Windows and Unix), we definitely prefer to use R whenever feasible (both for research and teaching). Thanks for developing a superb

Dear R users,, I'm having difficulties when i use the gstat extensions in R especially with the graphical interface, as the variograms plots are depicted with gray background and cyan points for the number of pairs, Consequently the fitted variogram is drawn in cyan, How can i change that so i could have, white background and black lines for the fitted variogram, for the complete plot.

Hello all, I am trying to use "clim.pact" package for my work, but since this is the beginning for me to use gridded datasets in "R", I am having some trouble. I want to do seasonal analyses like trends, anomalies, variograms, EOF and probably kriging too to downscale my 1 degree gridded data to 0.5.  So, as a first step, I compiled my entire dataset (with 25

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

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

I'm testing some different formulations of pairwise interaction point processes in Spatstat (version 1.11-6) using R 2.5.0 on a Windows platform and I wish to simulate them using the Metropolis-Hastings algorithm implemented with Spatstat. Spatstat utilizes Fortran77 code with the preprocessor RatFor to do the Metropolis-Hastings MCMC, but the Makefile is more complicated than any I have

Hello group, For my PhD I'm working on a spatial sampling grid. I do have two data sets which I'd like to compare using cross-correlograms or cross-variograms. Is this an option in one of the R-packages? I've been searching the R-help archive and the available package-documentations, but I can't find how to do this. Thanks in advance, Ren?.

Greetings, all I am having difficulty getting the fitdistr() function to return without an error on my data. Specifically, what I'm trying to do is get a parameter estimation for fracture intensity data in a well / borehole. Lower bound is 0 (no fractures in the selected data interval), and upper bound is ~ 10 - 50, depending on what scale you are conducting the analysis on. I read in the