similar to: kde2d error message

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

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, I'm trying to do a simple survival analysis on some data, and I'm having the following problem (here's my code and the error message): out <- Surv(fup,event=status) Error in Surv(fup, event = status) : argument "time2" is missing, with no default >From reading the documentation, it seems that I should be able to simply write: Surv(time1, event) if my data is

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

Hello, I'd be very grateful for help with some ggplot2's stat_density2d issues. First issue is with data limits. xlim() and ylim() doesn't seem to work; instead, estimates (and plotting) seems to be constrained to range(x), range(y) no matter what i do. The documentation says i can pass in kde2d's parameters to ... but pussing kde2d's "lims" parameter achieves

Hi Everyone, I think I found a problem with the ifelse function: If the condition argument is NA, it treats it as true. Anyone agree or disagree with this? Jen -- Jennifer Dillon Doctoral Student Harvard Biostatistics Room 414B, Building 1 [[alternative HTML version deleted]]

Hello, I am almost a total novice, and I am sure there must be an easy (and basic) way to turn a variable of 1's and 2's into a variable of zeros and ones. This is in a data frame, but if I could do it with vectors, that's all I need. Can someone tell me how? Thanks so much, Jen

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 <-

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

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, 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

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

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

Hello, This sounds like a problem to which many solutions should exist, but I did not manage to find one. Basically, given a list of datapoints, I'd like to keep those within the X% percentile highest density. That would be equivalent to retain only points within a given line of a contour plot. Thanks to anybody who could let me know which function I could use! Best, Emmanuel

Does anybody here have a suggestion for a clever way of creating contour plots for estimated bivariate density functions conditional on a factor? The contourplot function in the 'lattice' package only accepts data that are on the form 'z ~ x * y', not on the form 'x,y' or 'y~x'; otherwise I could probably have used the panel function to do the needed conversion.

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

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, The silverman's paper introduction offer how to find a mode for one dimensional data based on software http://www.stanford.edu/~kasparr/software/silverman.r, for two dimensional data I use kde2d to smooth it out first, then I get a matrix of densities for all the X(one dimension) cross Y(another dimension). I sort X and Y first before I pass the values to kde2d(x, y, c(hx, hy)), the

Hi, I posted a message earlier entitled "How to fit a line through the "Mountain crest" ..." I figured loess is probably the best way, but it seems that the problem is the robustness of the fit. Below I paste an example to illustrate the problem: tmp=rnorm(2000) X.background = 5+tmp; Y.background = 5+ (10*tmp+rnorm(2000)) X.specific = 3.5+3*runif(1000);

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