similar to: help in fortran code

Hi all, I have a data frame called "rst", see below: ------------------------------------------------------------------------------------------ # This is a paste able example # In case you don't have "KernSmooth" package installed, please uncomment below line. # install.packages("KernSmooth") library(KernSmooth) rst <- data.frame(hsp = rnorm(23), dal =

Dear Sir, Madam, or to whom this may concern, my name is Jan Failenschmid and I am a Ph.D. student at Tilburg University. For my project I have been looking into different types of kernel regression estimators and corresponding R functions. While comparing different functions I noticed that stats::ksmooth returned different estimates for the same bandwidth as other kernel regression estimators

Apologies in advance if my comments don't help, in which case, no need to respond, but I noted in ?ksmooth: "bandwidth the bandwidth. The kernels are scaled so that their quartiles (viewed as probability densities) are at ? 0.25*bandwidth." So, could this be a source of the discrepancies you cited? Given that ?ksmooth explicitly says: "Note: This function was implemented for

Updating my 1.8.0 R installation (>update.packages() ) I obtain the following (SORRY FOR THE LENGTH OF THE LOG BUT IT HELPS!!!): ................ downloaded 135Kb KernSmooth : Version 2.22-11 in /usr/lib/R/library Version 2.22-12 on CRAN Update (y/N)? y mgcv : Version 0.9-3.1 in /usr/lib/R/library Version 0.9-6 on CRAN Update (y/N)? y trying URL

Hi, just a quick question does dpill computes the bandwidth or half-bandwidth? The help says bandwidth, but in the literature there is often confusion between the bandwidth and half-bandwidth. thanks, Giacomo [[alternative HTML version deleted]]

I always followed http://cran.r-project.org/bin/linux/ubuntu/ to install R on Ubuntu 8.1. I had no errors before! > install.packages("XML") Warning in install.packages("XML") : argument 'lib' is missing: using '/usr/local/lib/R/site-library' --- Please select a CRAN mirror for use in this session --- Loading Tcl/Tk interface ... done trying URL

I have an inquire about the RNG in R It is known that when we use the " rnorm " function , we pass the arguments : 1- number of variables to be generated 2- mean vector of the normal random errors. 3- standard deviation vector of the normal random errors. my question is the following Is the a way (a function) in R that we could specify the covariance matrix in step 3, instead of the

is there a way of estimating derivative curves, similar to the ones we get from 'locpoly', from 'loess' estimation. i am interested in estimation of 1st and 2nd derivatives... --------------------------------- [[alternate HTML version deleted]]

Hi: I am using the package "KernSmooth" to do the local polynomial regression. However, it seems the function "locpoly" can only deal with univariate covaraite. I wonder is there any kernel smoothing package in R can deal with bivariate covariates? I also checked the package "lcofit" in which function "lcofit" can indeed deal with bivariate case. The

Dear R users, I am currently using the locpoly function from the KernSmooth package to estimate densities. However, I have some trouble understanding how this estimation technique is implemented in R. My main concern comes from the fact that this function gives negative estimates when the bandwidth is sufficiently large (mainly in the tails of distributions). I have read some articles on this

I was trying to install a package but received this error message: >R INSTALL KernSmooth_2.22-3.tar.gz Installing package `KernSmooth' ... libs g77 -fPIC -O2 -m486 -fno-strength-reduce -g -c blkest.f -o blkest.o make: g77: Command not found make: *** [blkest.o] Error 127 Must I have a fortran compiler to install R packages? Thanks for any advice, Rose Hoberman

Hello All, Is there a local bandwidth selection routine for local polynomial regression (locpoly) ? Thanks Chinthaka Kuruwita

Hello, I'm using R 1.40 on MacOS X X.1.2 (installed via the fink package manager). To upgrade my installed packages, I tried to use update.packages() today. All went well for most packages, with the exception of KernSmooth and cluster. In both cases, libraries were not found although I think they are present. Here's what happened: ---------------------------------- >

Full_Name: Jarno Tuimala Version: 2.3.1 OS: Solaris / Linux Submission from: (NULL) (193.166.2.98) Today I downloaded the latest source code release R-2.3.1.tar.gz, and it seems not to contain the VR bundle. After running ./configure I get the following error message: checking for recommended packages... ./src/library/Recommended/VR_*.tar.gz: No such file or directory no configure: error: Some

I had run into problems when compiling some contributed packages to an installation of R 1.40 by fink on MacOS X. Namely, packages KernSmooth (2.22-7) and cluster (1.4-0) would not find required libraries, though those were present on the system. Jeff Whitaker, the maintainer of the R fink packages, kindly sent me this: > Kaspar: It's not looking in /sw/lib, where the libs are (the

Dear list, I've got a question concerning difference between loess and locpoly. I have to use a plug-in method to chose a bandwith so I take locpoly method to fit a curve. My problem is:I know how to get predicted values in loess: m=loess(y~x) y_fitted=predict(m). But how to get the same in locpoly? I computed like this: bw=dpill(x, y, blockmax = 5, divisor = 20,trim = 0.01, proptrun =

In reference to the thread http://tolstoy.newcastle.edu.au/R/devel/04/10/0859.html I have the same problem updating packages with newly-installed version of released version of R 2.0.1. Previous posts refer to a bug in windows. I wonder if there is a work-around? This probably should go to R-help but it follows on from the post in R-devel. Apologies in advance. OS: Windows XP Professional,

Hi! Some weeks ago I discovered R. Now, I have a somewhat complicated task and am not sure whether R is the right tool to solve it. I got data of several series or measurements where I have to find the two inflection points. I did a linear regression (with ^2 and ^3 arguments), the problem there was that I had to look only at a very narrow band of measurement in order to get the

Dear R Users, When using locpoly function, number of output values is smaller than the number of input values. How is it possible to get number of output component $y equal to the number of inputs. Thanks a lot, Amir --------------------------------- [[alternative HTML version deleted]]

Hello!! At first thank you all for your suggestions and your help. But I would like to get another group of datas from the density estimation. I don't know if these information are provided by locfit or I should use an other function like plot(). Description: Each number between 1 and 100 (only integer) for example should have only one density value. But I also would like to have the density