similar to: Computing the mode

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such

Dear All, I'd like to know if it is possible to create animations with R. To be specific, I attach a code I am using for my research to plot some analytical results in 3D using the lattice package. It is not necessary to go through the code. Simply, it plots some 3D density profiles at two different times selected by the user. I wonder if it is possible to use the data generated for different

I'm sure there must be various peak-finding algorithms out there. Not knowing of any, I have written one myself*, but I thought I'd ask to see what's out there. Basically, I have a 2-dimensional data set and I want to identify local peaks in the data, while ignoring "trivial" peaks. My naive algorithm first identifies every peak and valley (point of inflection change

Hi, I was recently plowing through the docs of the quantreg package by Roger Koenker and came across the total variation penalty approach to 1-dimensional spline fitting. I googled around a bit and have found some papers originated in the image processing community, but (apart from Roger's papers) no paper that would discuss its statistical aspects. I have a couple of questions in this

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

Full_Name: Gerard Torrent Version: R version 2.8.0 (2008-10-20) OS: Linux 2.6.27.5-41.fc9.x86_64 #1 SMP Submission from: (NULL) (85.52.227.233) In some cases qt complains about NaNs and don't gives the correct result: > qt(0.1,, 0.1) [1] NaN Warning message: In qt(p, df, lower.tail, log.p) : NaNs produced But the result can be found: > pt(-1.60443e+06, 0.1) [1] 0.09999997 If I

Hello, Does anyone know how to write the files created by the call of "texi2dvi" in another directory ? Thanks, Matthieu

Hi all, I?m having some trouble when trying to compare character values (to check if they are alphabetically ordered). Is it possible to do it in any way? Thanks for your help. Cheers, Aurora

thanks to all for the 2d scatter plot. i have one more. how do i plot 'hist(y1, col="red") and hist(y2,col="blue") in the same window? thanks again.

Hi all, I have a sample of n values from a bivariate distribution (from a MCMC procedure). How could I draw a contour plot of "the joint density" based on that sample ? Sorry if I was not too clear. Thans in advance, Regards, Caio [[alternative HTML version deleted]]

Let me start by introducing myself as a biologist with only a little knowledge about programming in matlab and R. In the past I have succesfully created my figures in matlab using the hist3d command, but I have not access to matlab right now and would like to switch to R. I have used the plot command to create a figure of my data and it does almost what I want it to do. My data matrix looks like

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

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

Hi, guys, I need to simulate Pareto distribution. But I found 'rpareto' didn't exist in R. And it seems that Pareto distribution don't have mathematical relationships with other distributions. What can I do? Thanks a lot. Ni --------------------------------- [[alternative HTML version deleted]]

A friend and I were recently talking about the possible downfall of Internet radio, and as everyone seems to these days, decided that a nice solution would be to set up a P2P broadcasting solution. However, streaming has a completely different set of requirements than file sharing, with bandwidth and QOS become much larger issues. As such, we started to realize that a new audio compression scheme

Full_Name: Naoki Takebayashi Version: 0.65.0+R-release.diff (Oct 6, 1999) OS: Linux/Alpha Submission from: (NULL) (129.79.224.171) This will fix the "problem 2 (crash in fft)" in Bug ID #277 On Linux/Alpha, make check failed because R could not handle the following example in base-Ex.R ##___ Examples ___: # The Old Faithful geyser data data(faithful) : : ## Missing values: x <-

Hi all, I have tried to compute a p-value for a hypergeometric distribution as: dhyper(x,k,l,n) + phyper(x,k,l,n,lower.tail=FALSE) and sometimes obtained negative values. Do you know if it is because a round error or am I doing something wrong? Thanks in advance, Aurora

Dear all, quite a naive question: I have a data frame and I computed "the kernel density estimate" with density on each column. Now I'd like to export in a txt file the density function output for each column, but, when if I use write.table, I get a message "Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce class "density" into a

Dear developers, the current implementation of hist.default() calculates 'density' (and 'intensities') as dens <- counts/(n*h) where h has been calculated before as h <- diff(fuzzybreaks) which results in 'fuzzy' values for the density, see e.g. > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE) > print(tmp$density,digits=15) [1]