search for: anisotropy

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 my...

...("$", var=2, scale=2, list("exp")), list("$", var=1, list("nugget")) ) Ultimately I would like to work with anisotropic models (and data), and this is where I get confused. I can specify a model with (geographic) anisotropy by defining an anisotropy matrix, m and incorporating that into the definition: m = matrix( c(1,0,0,0.1), nrow=2) modelA=list("+", list("$", var=2, anis=m, list("exp")), list("$", var=1, list("nugget...

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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 -...

...rend): > beta0 beta1 > 0.0312 0.0024 > > Parameters of the spatial component: > correlation function: exponential > (estimated) variance parameter sigmasq (partial sill) = 0.0082 > (estimated) cor. fct. parameter phi (range parameter) = 797.1 > anisotropy parameters: > (fixed) anisotropy angle = 0 ( 0 degrees ) > (fixed) anisotropy ratio = 1 > > Parameter of the error component: > (estimated) nugget = 0.002 > > Transformation parameter: > (fixed) Box-Cox parameter = 1 (no transformation) &gt...

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....

...ndom data-set in the space 5. Fig 5 ? ordinary kriging: show a trend in the space (hypothesis: the points are very close in the space) 6. Fig 6 ?de-trend dataset with: v <- variogram (log(Z)~X+Y, subground, cutoff=1800, width=100)) 7. Fig 7 ? map of semi-variogram: show an anisotropy in the space (0? is Nord= 135? major radius 45? minus radius) 8. Fig 8- semi-variogram with anisotropy (0?, 45?, 90?, 135?). Best shape is from 135? 9. Fig 9- semi-variogram fit with Gaussian Model. R code is: > v = variogram(Z~X+Y, subground, cutoff=1800, width=200, alpha=c(13...

...aw=FALSE) #fails MAXNUMPTS plot(c(-50,50),c(0,1)) xspline(x,y,s,open=TRUE,repEnds=FALSE,border=2,lty=2) # OK-ish: red, but no dashes points <- xspline(x,y,s,open=TRUE,repEnds=FALSE,border=2,lty=2,draw=FALSE) # works I note from the help page that "Device coordinates are used (with an anisotropy correction if needed.)", so I assume the difference between the more complex cases which work and fail is to do with that, but I am stumped as to how to use that information! (The only help message mentioning MAXNUMPTS I can find is to do with grid.xspline, so I cannot use the solution sugges...

...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 estimation can be done using a linearized model, or using a non-linear model. A correction for Rician bias can be included. - -- Karsten Tabelow, Dr. WIAS Berlin Mohrenstrasse 39, 10117 Berlin, Germany email: tabelow at wias-berlin.de phone: +49-30-20372 564 fax...

...y good source for someone willing to use geostatistics in R. > > > > Regards > > > > EJ > > > > On Fri, 2003-01-17 at 05:06, Yan Yu wrote: > > > 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...

Hello R users, I have numerical data sampled on two grids, each one shifted by 0.5 from the other. For example: grid1 = expand.grid(x=0:3, y=0.5:2.5) grid2 = expand.grid(x=0.5:2.5, y=0:3) gridFinal = expand.grid(x=0.5:2.5, y=0.5:2.5) plot(gridFinal, xlim=c(0,3), ylim=c(0,3), col="black", pch=19) points(grid1, xlim=c(0,3), ylim=c(0,3), col="red", pch=19) points(grid2,

...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 estimation can be done using a linearized model, or using a non-linear model. A correction for Rician bias can be included. - -- Karsten Tabelow, Dr. WIAS Berlin Mohrenstrasse 39, 10117 Berlin, Germany email: tabelow at wias-berlin.de phone: +49-30-20372 564 fax...

Hi all, I've noticed that many computational neuroscience research groups use MATLAB. While it's possible that MATLAB may have some features unavailable in R, I suspect that this may instead simply be a case of costly tradition, where researchers were taught MATLAB as students and pay for it as researchers because it's all they know. I'd like to attempt to break the cycle by

Hi, my question is not exactly about R... What I am looking for are hints and directions on suitable methods (available in R or elsewhere) to solve a grouping (or pattern recognition) problem of environmental features in an environmental gradient as described below. Given environmental sampling data set (Depth, Presence of sand, Presence of boulders, Presence of clay). 1 1 1 0 1 1 0 0 1 1

Greetings, A couple general questions regarding the use of splines to interpolate depth profile data. Here is an example of a set of depths, with associated attributes for a given soil profile, along with a function for calculating midpoints from a set of soil horizon boundaries: #calculate midpoints: mid <- function(x) { for( i in 1:length(x)) { if( i > 1) { a[i] = (x[i] -

...alefff at gmail.com> License: GPL-3 http://crantastic.org/packages/SPSL SPSL package provides functionality for labeling of percolation cluster on 2D &amp; 3D square lattice with various lattice size, relative fraction of accessible sites (occupation probability), iso- &amp; anisotropy, von Neumann &amp; Moore d-neighborhood * tm.plugin.factiva (1.0) Maintainer: Milan Bouchet-Valat Author(s): Milan Bouchet-Valat <nalimilan at club.fr> License: GPL (>= 2) http://crantastic.org/packages/tm-plugin-factiva This package provides a tm Source to create corpora f...

...e and azimuth) vector analysis is performed in three stages: modules are analyzed by means of linear statistics, azimuths are analyzed by circular statistics, and the joint analysis of modules and azimuths is done using density maps that allow detecting another distribution properties (I.e. anisotropy) and outliers. Tests and circular statistic parameters have associated a full range of graphing: histograms, maps of distributions, point maps, vector maps, density maps, distribution modules and azimuths. * VHDClassification (0.2) Unknown http://crantastic.org/packages/VHDClassification...

...o format.AsIs() discarded dimnames, causing dataframes with matrix variables to be printed without using the column names, unlike what happens in S-PLUS (Tim Hesterberg, PR#10730). o xspline() and grid::grid.xspline() work in device coordinates and now correct for anisotropy in the device coordinate system. o grid.locator() now indicates to the graphics device that it is is in 'graphics input' mode (as locator() and identify() always have). This means that devices can now indicate the 'graphics input' mode by e.g....

...o format.AsIs() discarded dimnames, causing dataframes with matrix variables to be printed without using the column names, unlike what happens in S-PLUS (Tim Hesterberg, PR#10730). o xspline() and grid::grid.xspline() work in device coordinates and now correct for anisotropy in the device coordinate system. o grid.locator() now indicates to the graphics device that it is is in 'graphics input' mode (as locator() and identify() always have). This means that devices can now indicate the 'graphics input' mode by e.g....