similar to: 2d kriging with anisotropy on an irregular network (RandomFields Package)

Hello, I am presently trying to get a feel for the various packages out there that allow me to both analyze and simulate random fields. The package RandomFields is nice, but there are still a few aspects of its implementation that are confusing to me and I was hoping someone could help clarify things for me. It could also be that my questions reflect a lack of knowledge pertaining to random

Folks, I run R on a early 2009 MacBook Pro running Mountain Lion. I have a bunch of fonts in my user Library one of which is Garamond. I have tried the ttf_import function to no avail. I played with this for a couple of hours at least and I have gotten nowhere. Here is a bit of one of my sessions (note that I used file.choose to get down to the Font level) > require(extrafont) Loading

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Dear all, I wish to create a POSIXct variable from date and time variables using the ymd_hm function in package lubridate. In some cases data for time is missing, which causes a problem for ymd_hm. I wish to find a smooth way to handle this. # Some example data: x <- data.frame(date = c("2011-09-22", "2011-07-28"), time = c("15:00", NA)) x # paste date and

Dear R-bug-people I have encountered a problem with "unsplit", which I believe may be caused by a bug in the function. However, unexpericend with bug-reports I apologise if this is barely a user problem rather than a problem within R. The problem occurs if an object is split by several grouping factors with levels not occuring in the data, and using drop = TRUE. This may appear as

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

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

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

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

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++

This is release 0.9.60 of Wine, a free implementation of Windows on Unix. What's new in this release (see below for details): - Better support for Windows IMEs. - Option for Windows-style window decorations. - Improved system tray behavior. - Window management fixes. - Improved quartz audio support. - Better support for launching apps from Unix file managers. - Lots of bug

The Wine development release 1.4-rc3 is now available. What's new in this release (see below for details): - Bug fixes only, we are in code freeze. The source is available from the following locations: http://ibiblio.org/pub/linux/system/emulators/wine/wine-1.4-rc3.tar.bz2 http://prdownloads.sourceforge.net/wine/wine-1.4-rc3.tar.bz2 Binary packages for various distributions will be

How do people deal with R and memory issues? I have tried using gc() to see how much memory is used at each step. Scanned Crawley R-Book and all other R books I have available and the FAQ on-line but no help really found. Running WinXP Pro (32 bit) with 4 GB RAM. One SATA drive pair is in RAID 0 configuration with 10000 MB allocated as virtual memory. I do have another machine

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 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

Hi If you read the description of "varcov.spatial" you'll see that it is used to *predict* a covariance matrix, based on the parameters of the covariance function. So you don't need the oebserved data, you need parameters for the covariance function. Regards EJ On Thu, 2003-04-17 at 05:43, Yan Yu wrote: > THanks for the suggestion. > I have a Q when trying to use it..

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 dti is a new contributed package for R, that implements functions for smoothing Diffusion-weighted MR data with structural adaptive smoothing methods. Version 0.5-2 contains functions for smoothing DW data in the context of the Diffusion Tensor Model and for visualization of Diffusion Tensor Data and anisotropy maps derived thereof. The tensor

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 dti is a new contributed package for R, that implements functions for smoothing Diffusion-weighted MR data with structural adaptive smoothing methods. Version 0.5-2 contains functions for smoothing DW data in the context of the Diffusion Tensor Model and for visualization of Diffusion Tensor Data and anisotropy maps derived thereof. The tensor

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