similar to: Joint density kde2d works improperly?

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

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 <-

Problem: Based on a n x 2 data matrix i want a kernel estimate of the bivariate density. However, i also wish to specify wich points the density should be calculated at. I can offcourse just write the full kernel density estimate as a R-code, but surely there must already exist some package for this operation? The package density(), seems to create a new matrix (depending on n), where the

Dear all, does anybody ever encountered the problem with diagnostic plots? x<-rnorm(100) y<-rnorm(100) plot(lm(x~y)) It gives the following message "Waiting to confirm page change..." and nothing happens. Thanks a lot! [[alternative HTML version deleted]]

Hello! I am trying to do a smooth with the kde2d function, and I'm getting an error message about NAs. Does anyone have any suggestions? Does this function not do well with NAs in general? fit <- kde2d(X, Y, n=100,lims=c(range(X),range(Y))) Error in if (from == to || length.out < 2) by <- 1 : missing value where TRUE/FALSE needed Thanks in advance!! Jen [[alternative

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

Hallo I am trying to use the package LocFit to follow the example given in an Introductory note of C Loader concerning density estimation. It involves the "geyser" dataset (107 observations on durations, inlc in the package). I have tried the following (using the latest version of R): fit.of <- locfit(~geyser,flim=c(1,6),alpha=c(0.15,0.9)) plot(fit.of,get.data=T,mpv=200) This

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

Good evening, I am Marta Colombo, student at Milan's Politecnico. Thank you very much for your kindness, this mailing list is really useful. I am using the function kde2d for two-dimensional kernel density estimation and I'd like to know something more about this kind of density estimator. In particular I'd like to know: what bandwidth is used ? Thank you in advance for your attention

Hallo, I want to use kde2d to visualize data on a sphere given in spherical coordinates. Now the problem is, that "phi == 2*pi = 0", so in principal I have to connect (in a graphical view) the left and right border of my plot (and the bottom and top). Has anyone any idea how to do that ? Thanks, Manuel -- ------------------------------------- Manuel Metz Sternwarte der

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

Hi everybody, well, I definitely don't understand anything. Why the hist function with freq=FALSE gives such a strange result??? R <- c(-1.10, 0.79, -1.17, -0.53, -0.26, -0.22, 0.29, -0.26, -0.26, 0.39) hist(R, freq=FALSE, breaks=10) Thanks everybody [[alternative HTML version deleted]]

Dear all, might seem and easy question but I cannot figure it out. floor(100*(.58)) [1] 57 where is the trick here? And how can I end up with the right answer? Thanks a lot everybody for your help. Trafim [[alternative HTML version deleted]]

Dear all, Does anybody know the probable reason why <= gives false when it should give true? These two variables are of the same type, and everything works in the cycle but then it stops when they are equal. this is the output result > Rk[47] <= RB[21] [1] FALSE > Rk[47] [1] 0.002842007 > RB[21] [1] 0.002842007 Thanks a lot. [[alternative HTML version deleted]]

Hi, I am wondering if the kde2d 2-D kernel density estimation function in the MASS package can take into account the effect of correlations between the variables. I couldn't find any achieved information on this issue. Unfortunately, I don't have the 2002 edition of Modern Applied Statistics with S by Venables and Ripley in case it was described there. Thanks in advance. Adam

Dear all, I have a question is there a possibility to plot points with different symbols like stars, crosses? I looked at different types for plot command and didn't find anything like that. Thanks a lot. [[alternative HTML version deleted]]

Dear all, does anyone know how to define the structure of the required samples using function createDataPartition, meaning proportions of different types of variable in the partition? Smth like this for iris data: createDataPartition(y = c(setosa = .5, virginica = .3, versicolor = .2), times = 10, p = .7, list = FALSE) Thanks a lot for your help. Regards, Trafim [[alternative HTML version

Dear all, Are there any functions in R to reverse the order of the string. smth like reverse("abc") to get "cba"? Thanks a lot. [[alternative HTML version deleted]]

Hi, I guess I have a naive question. I use kde2d function in a standard way to estimate kernel densities of x and y (x and y are vectors) and plot them using image(). f1=kde2d(x,y) image(f1) But what if I want to see kernel estimates of three variables, x, y and z (a vector) plotted together ? Something in which x<->y is plotted and colored according to the corresponding value of z ?

Dear all, I would like to ask you if there is a possibility in R to give the names to graphs which are not const. For example, How to name each plot, or to add notes like a=x[i], b=y[i] in this cycle x<-c(1,2,3,4,5,6) y<-c(7,8,9,10,11,12) par(mfrow=c(2,3)) for (i in 1:6){ plot(x,y) } Thank you for your time and help! [[alternative HTML version deleted]]