similar to: Isocontour-lines of spatial data on a rectangular grid (not plots!)

Hi there, I have two data sets, one of locations at different elevations (x,y,z) and the other of points that make up topographic contours (also x,y,z). I have used: result<-apply(distppll(data2,cbind(topocon[-nrow(topocon),],topocon[-1,])),1,min) where 'data2' are my measurement coordinates (x, y) and 'topocon' are my topographic contours (x,y). While this gives me an output

Dear R-helpers, I'd like to be able to post-process contours coming from contour(). Does anyone have a version of contour() (or something similar) which will return the contour coordinates? In searching the archives I've come across a message in Nov 01 which had this on a wish-list, but I can find no later reference. With thanks, John Field Adelaide, South Australia

Hi All- I would like to create a 3d topographic map using lat/lon and z(height). I have been scouring the R help pages and have not located the package I am looking for. Does anyone have a suggestion of package that will work for this? thanks- sherri

Hi all, If I use a moving average, it will smooth the choppy time series, but it will lead to lagging... How do I smooth timeseries without the lagging effect? Thanks!

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a rectangular matrix of size 920 by 85. I'd like to coerce it into a square matrix such that all row/col names are present in the new matrix and the additional values are zero. As an example: A B C D A 1 2 3 4 E 5 6 7 8 F 9 10 11 12 Would be coerced to: A B C D E F A 1 2 3 4 5 9 B 2 0 0 0 6 10 C 3 0 0

... finding myself doing this by hand one too many times ... maybe someone else has found a nice general solution ... I have a data frame containing n rows on p+q variables which I will call p.1, p2, ..., pp and q1, q2, ... qq. For simplicity all of these variables are continuous numeric. I want to create the following arrangement of plots: A scatterplot matrix which contains p times q panels

Dear All, I would like to plot a scalar (e.g. a temperature) on a non-rectangular domain (or even better: I would simply like to be able to draw a contour plot on an arbitrary 2D domain). I wonder if there is any tool to achieve that with R. I did some online search in particular on the list archives, found several queries similar to this one but was not able to find any conclusive answer. I

Dear list members I'm currently working on some topographic (elevation) data, and was somewhat surprised that the 'topo.colors' and 'terrain.colors' are of little to no use here. The problem is that these functions only return a palette of colours; they don't map depth values to colours. So if I plot (using 'image', 'persp' or similar functions) and

Bare test code: My simple Java test class source and R test code follow: public class RJavTest { public static void main(String[]args) { RJavTest rJavTest=new RJavTest(); } public final static String conStg="testString"; public final static double con0dbl=10000001; public final static double[]con1Arr=new double[] { 10001,10002,10003,10004,10005,10006 }; public final static

In an experimental setup we obtain z-data samples at equidistant grid points. The surf.gls (Kriging) algorithm produces an error under this circumstance when performing the Choleski decomposition. A workaround is to dither the grid coordinates using (x <- rnorm(length(x)) ; y<- rnowm(length(y))). Question: Is this an expected behaviour of the surf.gls function ? Regards, Berthold

I tried to use R version of package I noticed the original MatLab Pckage is much better documented. I had a look at the R demo code "gtm_demo" and found that variable Y is used in advanced of being created: I wrote my own few lines as follows: inDir <- "C:/Documents and Settings/Monville/Alanine Dipeptide/DBP1/DHA" setwd(inDir) T <-

Dear useRs, I got stuck trying to generate a palette of topographic colors that would satisfy these two requirements: - the pallete must be 'anchored' at 0 (just like on a map), with light blue/lawn green corresponding to data values close to 0 (dark blue to light blue for negative values, green-yellow-brown for positive values) - the brown must get darker for higher positive

Hi, I have matrix of sea bottom depths that I am plotting in R with the function 'image'. I am particularly interested in the 200m depth contour (I'm using 'distance from this feature' as a covariate in a model) and would like to extract the data at evenly spaced points along it. I can easily superimpose a line at 200m using the function 'contour'. What I want to

Hi all, I'm fairly new to R, so I'm still trying to feel out what is available to me. I would like to be able to plot joint density in a two dimensional plot where density is indicated by color or darkness gradients, like a 2d color coded topographic map. Ideally, the output would be something I could then plot other points or lines on. Currently, I'm calculating joint density with

Dear all, I am looking for a clustering method usefull to classify the countries in some clusters taking account of: a) the geographical distance (in km) between countries and b) of some macroeconomic indicators (gdp, life expectancy...). Are there some packages in R usefull for this? Thanks a lot for your help, Dorina

We have extracted parameters from physiological measurements by fitting SSlogis-like curves with nlsList and nlme. We presented residuals plot in a paper, but a referee argues that these cannot be included (too technical), and r-square values should be given instead to compare the goodness of fit with those of other authors. I remember that 30 years ago in my stat 101, I learned that r-square is

I can't get the PERL subexpression translated to R. Following, for example, B. Ripley's http://finzi.psych.upenn.edu/R/Rhelp02a/archive/58984.html I am using sub, but it looks like an ugly substitute. Assume I want to extract the first alpha part and the first numeric part, but only if they are in sequence. Do I really have to use the sub twice, first extracting the first variable, then

Hi there, I hope I can get advice regarding the calculation of leverage values or studentized residual values of a non-linear regression model. It seems like rstudent() does not work on a nls object. Many thanks in advance! Best regards, Xingli

Dear List, creating factors in a given non-default orders is notoriously difficult to explain in a course. Students love the ifelse construct given below most, but I remember some comment from Martin M?chler (?) that ifelse should be banned from courses. Any better idea? Not necessarily short, easy to remember is important. Dieter data = c(1,7,10,50,70) levs =

Dear R and lme4 users- I am trying to fit a mixed-effects model, with the glmer function in lme4, to right-skewed, zero-inflated, non-normal data representing understory grass and forb biomass (continuous) as a function of tree density (indicated by leaf-area). Thus, I have tried to specify a Gamma distribution with a log-link function but consistently receive an error as follows: >