similar to: Conditional contour plots for estimated density functions using Lattice

My R installation (Mac OS9.2.2) is working, but when I try to run the examples from Venables & Ripley (p. 6): R : Copyright 2001, The R Development Core Team Version 1.4.0 (2001-12-19) ... > library(MASS) > x<-rnorm(1000) > y<-rnorm(1000) > truehist(c(x,y+3),nbins=25) % Plots nicely > dd<-con2tr(kde2d(x,y)) % Doesn't complain > contourplot(z ~ x + y,

Hello, I am in need of help in putting histograms on the diagonal of a plot produced with splom(). The plot matrix I am trying to produce is to have standard scatterplots in the upper-left triangle, contour plots in the lower-right triangle, and histograms on the diagonal. I have a function that does the first two, but the histograms on the diagonal has been beyond my ability. Here is my

Dear R-help! I need to draw contour lines in a plot of wave heights (Hs) versus peak periods (Tp) showing the joint probabilities of 1-year wave heights~peak periods, 10-year wave heights~peak periods and 100-year wave heights~peak periods. I've used the contourplot() function in the plot I've added in this mail. You can use the added dataset "Rhelpdata.txt" to reproduce a

Dear R-help. When plotting 3D wireframe plots with the lattice package, there is often a lot of space between the actual plot (i.e., cube) and panel borders. For a single wireframe, this is not a problem, but when plotting multiple wireframes, the wasted space decreases the size of the plots very much. Is there a way to decrease this space/margin? I could not find any information about it in

I am a physician examining an NHANES dataset available at the NCHS website: http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/demo_d.xpt http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/hdl_d.xpt http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/tchol_d.xpt Thank you to the R authors and the foreign package authors in particular. Importing from the SAS export

Hi all We are pretty new to R here and trying to achieve something that we believe is possible but it?s not easy to work out how to do it. We are producing scatterplot matrices for e.g. 10 variables. What we would like to do is superimpose 2D kernel density estimators on top of each plot so that we end up with a scatterplot matrix of 2D kernel density (contour) plots. The kernel density plots

Estimate region of highest probabilty density Dear R-community I have data consisting of x and y. To each pair (x,y) a z value (weight) is assigned. With kde2d I can estimate the densities on a regular grid and based on this make a contour plot (not considering the z-values). According to an earlier post in the list I adjusted the kde2d to kde2d.weighted (see code below) to estimate the

Hello I'm trying to calculate 2d confindence bounds into a scatterplot using the function "kde2d" (package MASS) and a contour plot. I found a similar post providing a solution - unfortunatly I do not realy understand which data I have to use to calculated the named "quantile": Post URL: http://tolstoy.newcastle.edu.au/R/help/03b/5384.html > (...) > >> Is

Dear wizaRds, I use the MASS::kde2d function to estimate density of the two first principal components. I do that to have a graphic visualisation of a "group structure" in my dataset. So far, no problem. But i would like to estimate that density using weights according to the COS?? values that tells me if my observation is well represented on the factorial plan 1-2. I would like to

Hi, one of the nice things about contour is that it labels all contour lines. contourplot only labels each particular elevation a single time. i.e., if there are two contour lines corresponding to z = 45, it will only label one of them. is there a way to get contourplot to automatically label all the contour lines, even those that are repeated? i ask because i want to plot contour plots *w/

Dear R users, I used sm.density function in the sm package and kde2d() in the MASS package to estimate the bivariate density. Then I calculated the Kullback leibler divergence meassure between a distribution and the each of the estimated densities, but the asnwers are different. Is there any difference between the kde2d and sm.density estimates? if there is a difference, then which is the best

Folks, A few days ago, I had asked a question on this mailing list about making a contour plot where a function z(x,y) is evaluated on a grid of (x,y) points, and the data structure at hand is a simple table of (x,y,z) points. As usual, R has wonderful resources (and subtle complexity) in doing this, and the gurus of the list showed me the way. Here's a complete working example. One might

Hi All, I'm having difficulty making a contour plot a would like some help. A standard contourplot can be made by having an x,y, and some matrix (shape x*y) with contents: x = 1:10 y = 1:10 cont <- matrix(runif(100,min=1,max=2),nrow=10,ncol=10) filled.contour(x,y,cont) Looks very nice. Sometimes data comes in a different format however. Basically an x and an y, and a vector z with all

Hi, I have done the interpolation for my data and I was able to create the contours in multipanel with the help of Pascal. Now, I want to clip the contour with the shapefile. I want only the portion of contour to be displayed which falls inside the boundary of the shapefile. The data mydata.csv can be found on https://www.dropbox.com/s/khi7nv0160hi68p/mydata.csv The data for shapefile can be

Dear all, Please, look at the following code: attach(geyser) f1 <- kde2d(duration, waiting, n = 5) a <- 0 for (i in 1:5){ for (j in 1:5){ a <- a + f1$z[i,j] } } As far as I understood from Help kde2d returns matrix elements of which are values of joint probability mass function Pr(X=x,Y=y) therefore, sum of its elements should sum to 1. Which is not the case from my check. Where is

Phil, You write: >> Using x,y, and z variables in the enclosed test.RData, the command >> >> contour(x,y,z) >> >> produces a lovely 2D plot, whereas >> >> contourplot(z~x*y) >> >> produces the error.. >> >> Error in if (lim[1] > lim[2]) stop("Improper value of limit") : >> missing value where

Hello, I am a little bit confused regarding the density values obtained from the function kde2d() from the package MASS because the are not in the intervall [0,1] as I would expect them to be. Here is an example: x <- c(0.0036,0.0088,0.0042,0.0022,-0.0013,0.0007,0.0028,-0.0028,0.0019,0.0026,-0.0029,-0.0081,-0.0024,0.0090,0.0088,0.0038,0.0022,0.0068,0.0089,-0.0015,-0.0062,0.0066) y <-

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

I have four large two-dimensional matrices of which I want to create contour plots. Something like filled.contour(<matrix>) contourplot(<matrix>) works but only gives me one plot at a time. If I combine the four matrices into one three-dimensional matrix, which I'll name "seven", there should be a way of doing something like this contourplot(seven[,,k] for k in 1 to 4)

Friends, I have two covariance matrices (m1 and m2) of same size (150x150). I used contourplot function to make contour plots individually (c1 and c2). I am interested in making one contourplot overlapping the two individual contours so that the portion of the plot above and below the diagonal can represent the c1 and c2. Someone suggest me how can i do the same. Is there any way that i can