similar to: 3d plots?

Dear R users: I have a dataset with two variables (>20000 observations, two samples from same subject) and I used "kernSur" from library(Genkern) to get a estimated bivariate density and corresponding plots as follows: new.data.normal<-data.normal[!is.na(data.normal[,2]),] x<-new.data.normal[,2] y<-new.data.normal[,3] op <- KernSur(x,y, xgridsize=50, ygridsize=50,

I am having trouble getting smooth-appearing curves in figures produced as windows metafiles using R (R-1.1.1 on Windows 98). When I import them into a word processor (either MS Word 97, or WordPerfect 9.0), the figures appear only slightly bumpy on screen, but when printed, there is a clear jaggedness reminiscent of aliasing. Is there a fix for this (if the answer is "upgrade to 1.2",

Can somebody please take a look at this and tell me whats going wrong? It seems to be parsing wronly around the 'if' statement and gives me a directory listing. Thanks in advance Tom N.B. datan is an invented dataset xvals<-c(1,0.4,0.2) datan<-data.frame(s1=c(3,4,5),s2=c(5,5,5),s3=c(21,55,34),s4=c(5,3,2)) datan$sint<-NA datan$sgrad<-NA for(icount in 1:dim(datan)[1]) {

Hej, Calling newuoa (from the minqa package) makes R crash when the package rgl is loaded first. This however only on certain selected data. The data used for testing (saved to 'bugs.R'): xvals = c(1,2,4,5,7,8,9,10,11,12,14,15,16,18,19,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36) yvals =

Is there code for bivariate kernel density estimation? For bivariate kernels there is kde2d in MASS kde2d.g in GRASS KernSur in GenKern (list probably incomplete) but none of them seems to accept a weight parameter (like density does since R 2.2.0) -- Erich Neuwirth, University of Vienna Faculty of Computer Science Computer Supported Didactics Working Group Visit our SunSITE at

Dear all I'm a newbie regarding netcdf data. Today I realized that I maybe do not understand some basics of the netcdf. I want to create a *.nc file containing three variables for Switzerland. All data outside of the country are NAs. The third variable is calculated from the first two variables. Basically there is no problem to do that. I copy the file with the data of the first variable,

Hello list, I just started R today and tried something quite simple. I wanted to create a colored plot and eventually after hours of fiddling around got it working. However, my solution seems very suboptimal and I'd really appreciate your hints on how to improve. I believe that R already offers many functions I coded (e.g. distance between two vectors, vector length, vector normalization and

Hello, Using this data: http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt and the following code i got the image at the end of this message: US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep=" ") US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE)

Dear R-list, I'm iterating several calls to plotCI [gplots], like so: plotCI( x = xvals.f[sorted], y = yvals.f[sorted], xlim = c(xmin, xmax), ylim = c(ymin, ymax), pch = plot_symbols[graph_idx], type = "b", lty = plot_linetypes[1], col = plot_colors[graph_idx], barcol = plot_colors[graph_idx], uiw = NA, xlab = "", ylab = "", add =

On Mon, Aug 14, 2017 at 5:29 AM, <raphael.felber at agroscope.admin.ch> wrote: Dear all > > I'm a newbie regarding netcdf data. Today I realized that I maybe do not > understand some basics of the netcdf. I want to create a *.nc file > containing three variables for Switzerland. All data outside of the country > are NAs. The third variable is calculated from the first two

Hi Spencer, I have seen your name on the web site, and perhaps you can help me with my R problem. I'm trying to use KernSur to put in evidence a substructure in a bidimensional plot. My problem is that, in order to get the density in the low density areas (in which the substructure is located) I should use different bandwidths. How I can do that? Also, I think that the best choice for my

Full_Name: TOBY MARTHEWS Version: 2.1.1 OS: Windows XP Submission from: (NULL) (139.133.7.38) I think you should have better examples on the ?plot man page, if you don't mind me saying. Can I suggest something like this, which would probably stop so many emails to the R help about how to put on error bars Cheers, Toby M ****************************** xvalsT1=1:3 yvalsT1=c(10,20,30)

Dear list, I have multiple (BWidget) listboxes in the same toplevel window. The problem is, if I select (by left clicking) on one of those listbox elements, the current selection in the *other* listboxes is cleared! Anybody knows how I can prevent this? Here's my code (sorry not complete): (E.g. If I select an X value, I'd lose the Y value I selected before) gui.create.tab.general <-

Dear List, I'm using interp() to prepare 3d data for plotting with the contour() function. If have x,y and z data. All are arrays. X and Y are sampled in an orderly fashion on a grid (a circular sub-area of a grid - see plot). I'm trying to use interp() to get x and y arrays and a z matrix that can be fed to contour(). This is the command:

Dear Sir/Madam; Would you please tell me what is the command that allows the estimation of the Kernel Density for some data. Thanks, Thami Rachidi [[alternative HTML version deleted]]

Hi, have anybody a hint how i could avoid the cumbersome way (..especially the value part) change the data representation from n column data.frame to an stacked representation. many thanks Christian #example data dfw <- as.data.frame(matrix(runif(10*10),ncol=10)) dfw$group <- sample(c("X","Z"),nrow(dfw),replace=T,prob=c(0.75,0.25)) # change var <-

Hello, I am having a bit of trouble with scatterplot3d(). I was able to plot a 3d cloud of points using the following code: >my.3dplot<-scatterplot3d(my.coords, pch=19, zlim=c(0,1), scale.y=0.5, angle=30, box=FALSE) where my.coords is a data frame that contains x, y, and z coordinates for grid points whose elevation we sampled. The problem occurs when I try to add points using points3d.

Hi this is my first post. I am trying to run a simulation for a computer playing Von Neumann poker and adjusting it's expectation of an opponent's behavior according to how the opponent plays. This program involves random generation of "hands" and shifting of parameters. However, when I run the code, no errors come up, but the program doesn't do anything. Could someone

Dear R list, Can anyone help with a plotting question? I'm trying to display some data on a plot and I've almost got the format I need (see code below), but 2 things I can't get: 1. How to get "Jan","Feb","Mar" on the x=axis instead of 1:3? 2. How to get "T"s on the end of my error bars like you have in standard scientific plots? Any comments

How can I condition any error bar function that use the arrows() function, such as 'CI.plot' (see example below) or 'error.bars', to draw only upper error bar (upper CI) if the bar value (mean) is positive and the lower error bar (lower CI) if bar value is negative? CI.plot <- function(mean, se,length, ylim=c(-5, max(CI.H)), ...) { CI.H <- mean+se CI.L <- mean-se