similar to: range and anisotropy with RandomFields

Dear List I am using the RandomFields package, and I have a problem when 2d-kriging, with an anisotropy, some values from an irregular network. It works well when : - 2d-kriging, without any anisotropy, some data from an irregular network - 2d-kriging, with and without anisotropy, some data from a regular network - 3d-kriging, with and without anisotropy, some data from a regular network Here is

Hi, I'm having some difficulty installing the RandomFields package in R 1.7.0 under FreeBSD. I've installed the geoR package with no difficulties. Following are the errors that I get: * Installing *source* package 'RandomFields' ... ** libs c++ -I/usr/local/lib/R/include -I/usr/local/include -mieee-fp -fPIC -O -pipe -c MPP.cc -o MPP.o c++ -I/usr/local/lib/R/include

I have been unable to install the package RandomFields. I am using R 2.9.0-4 on Ubuntu 9.04. To install, I use the command: sudo R CMD INSTALL RandomFields_1.3.37.tar.gz The output follows below. Any help Would be appreciated. D. Hoysak Brandon University * Installing to library ?/usr/local/lib/R/site-library? * Installing *source* package ?RandomFields? ... ** libs g++

I have been unable to install the package RandomFields. I am using R 2.9.0-4 on Ubuntu 9.04. To install, I use the command: sudo R CMD INSTALL RandomFields_1.3.37.tar.gz The output follows below. Any help Would be appreciated. D. Hoysak Brandon University * Installing to library ?/usr/local/lib/R/site-library? * Installing *source* package ?RandomFields? ... ** libs g++

Hi cross posting from sig geo , because I really need help! I'm using geoR for some spatial linear models and I'm getting surprisingly optimistic values from the spatial models relative to the non-spatial, even when the models appear to be performing about equally (by AIC comparison) For example This model relating encounter rates of lizards to a soil substrate parameter gives >

Hi, Please see the email exchanges below. I am having trouble generating output that is large enough for our needs, specifically when using the GaussRF function. However, when I wrote Dr. Schlather (the author of the GaussRF function), he indicated that there is also a limit imposed by R itself. Is this something that we can overcome? Thank you very much for any assistance you may provde.

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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

Hi, all, Have anyone used kringing included in R? How is it? Does it handle anisotropy data well? How does it compare with Kriging in Arc/Info? or other geostatistics software customized to do kriging or other geostatistics functions? I tried Easykriging, a geostatistics tool developed for Matlab. It has very nice GUI, but it does not provide library which i can call in my programs. so it is

Hi, I have here a problem I''ve been working at for a little while but I can''t seem to get the error messages to appear correctly. My form looks something like this for "ModelA": [errors_for "modelA"] [form for "modelA"] [text "modelA" "fieldname1"] [text "modelB" "fieldname2"] [submit] [/form] The reason

Not really a bug (I eventually discovered), but ... When running GaussRF()/DoSimulateRF() with n>1, the default pch="!" prints backspaces to the terminal, which causes problems (LaTeX barfs) if you're running this within an Sweave() job. Setting RFparameters(pch="") fixes the problem. Could put this in the documentation, but I don't know where you could

The package list was accessed October 28, 10:13 am MST using Windows XP and mirror USA (CA 1). Bill Morphet, Ph.D.

Hi, I'm using RF to simulate a correlated variable with GaussRF set.seed=1 GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2)) However when I simulate again using the same random seed I get different results. > set.seed=1 > summary(GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2))) Min. 1st Qu. Median Mean 3rd

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

Currently, the cube plugin uses mipmapping only when cube is unfolded. When the cube is rotated, mipmaps are not used, which leads to ugly look of textures. The attached patch fixes this. This leads to another kind of artifacts, which are fixable with anisotropic filtering. http://team.pld-linux.org/~wolf/aniso.png The leftmost image is the current state of cube plugin. The center image is with

Hi! AFAIK FGLRX doesnt support glx_ext_texture_from_pixmap, and enabling composite+dri is resulting in screen corruption even with 8.38.6. Then how are you guys running it without XGL? Regards, Karthik On 6/29/07, compiz-request at lists.freedesktop.org < compiz-request at lists.freedesktop.org> wrote: > > Send compiz mailing list submissions to > compiz at

Dear R community, I have a fairly large file with variables in rows. Every variable (thousands) needs to be regressed on a reference variable. The file is too big to load into R (or R gets too slow having done it) and I do now read in line by line with "scan" (see below) and write the results to out. Although improved, this is still very slow... Can someone please help me and suggest

I am trying to work my way through the book "Singer, JD and Willett, JB, Applied Longitudinal Data Analysis. Oxford University Press, 2003" using R. I have the SAS code and S-Plus code from the UCLA site (doesn't include chapter 8 or later problems). In chapter 8, there is a structural equation/path model which can be specified for the sem package as follows S <- cov(al2)

Hi I'm interested in doing a anisotropy analysis of some spatial data and I want to do a contour plot of a covariance or variogram surface to visualize the directions of maximal and minimal anisotropy. I know how to do a contour plot :-) but how can I obtain the variogram surface having a geoeas format dataset (X, Y, Z) ? Thanks EJ

Hello all, I have two comboboxen, comboA is popultaed when :controller/list is retrieved first time. When comboA is selected, I want to auto-populate comboB (modelB belongs_to modelA). The population of tableC (modelC belongs_to modelB and belongs_to modelA) should not populate until a "GO" button is clicked (link_to with submit). Help? I need an example of how to filter the post