similar to: storage mode error question (R2winBUGS)

hello, i'm having a wierd problem with 0.31 tftpd-hpa. i'm using xinetd, with this config: service tftp { disable = no socket_type = dgram wait = yes user = root log_on_failure += USERID bind = 10.13.0.254 server = /usr/sbin/in.tftpd

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.20-0). Version 0.20-0 is documented in Tristen Hayfield and Jeffrey S. Racine (2008). Nonparametric Econometrics: The np Package. Journal of Statistical Software 27(5). URL http://www.jstatsoft.org/v27/i05/ and also in a vignette (vignette("np",package="np")). There is also a FAQ

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.20-0). Version 0.20-0 is documented in Tristen Hayfield and Jeffrey S. Racine (2008). Nonparametric Econometrics: The np Package. Journal of Statistical Software 27(5). URL http://www.jstatsoft.org/v27/i05/ and also in a vignette (vignette("np",package="np")). There is also a FAQ

Dear useRs, We are pleased to announce that versions 0.50-1 of the np package and its MPI-aware counterpart, the npRmpi package, are now available on CRAN: http://cran.r-project.org/web/packages/np/index.html http://cran.r-project.org/web/packages/npRmpi/index.html In these versions we add new functionality: - new methods for multivariate mixed-data bandwidth selection for unconditional and

Dear useRs, We are pleased to announce that versions 0.50-1 of the np package and its MPI-aware counterpart, the npRmpi package, are now available on CRAN: http://cran.r-project.org/web/packages/np/index.html http://cran.r-project.org/web/packages/npRmpi/index.html In these versions we add new functionality: - new methods for multivariate mixed-data bandwidth selection for unconditional and

Dear R users, A parallel implementation of the np package titled `npRmpi' is now available on CRAN. This package can take advantage of multiple core computing environments to reduce the run time associated with the methods contained in the np package. Kindly see the vignette for details and examples on modifying np code and running it in a parallel environment. You are requested to seek

Dear R users, A parallel implementation of the np package titled `npRmpi' is now available on CRAN. This package can take advantage of multiple core computing environments to reduce the run time associated with the methods contained in the np package. Kindly see the vignette for details and examples on modifying np code and running it in a parallel environment. You are requested to seek

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

Dear R users, Version 0.30-1 of the np package has been released and uploaded to CRAN. The np package provides nonparametric kernel smoothing methods for mixed data types. We encourage anyone using the package to upgrade to the latest version. Description: This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered,

Dear R users, Version 0.30-1 of the np package has been released and uploaded to CRAN. The np package provides nonparametric kernel smoothing methods for mixed data types. We encourage anyone using the package to upgrade to the latest version. Description: This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered,

Hi, I've got an ugly but fairly simple function: mdevstdev <- function(a){ l <- dnorm(a)/(1-pnorm(a)) integrand <- function(z)(abs(z-l)*dnorm(z)) inted <- integrate(integrand, a, Inf) inted[[1]]/((1- pnorm(a))*sqrt((1 + a*l - l^2))) } I wanted to quickly produce a graph of this over the range [-3,3] so I used: plotit <-function(x=seq(-3,3,0.01),...){

Hi, I've been running some simulations for a while and the performance of R has been great. However, I've recently changed the code to perform a sort of chi-square goodness-of-fit test. To get the observed values for each cell I've been using table() - specifically I've been using cut2 from Hmisc to divide up the range into a specified number of cells and then using

Dear people, I'm trying to do some analysis of a data using the models by Royle & Donazio in their fantastic book, particular the following function: http://www.mbr-pwrc.usgs.gov/pubanalysis/roylebook/panel4pt1.fn that applied to my data and in the console is as follows: > `desman.y` <- structure(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3",

Salve, till the 28. August midnight the magazin c't has a codec test between AAC, MP3, WMA and Vorbis Ogg online. http://www.heise.de/ct/leserbefragung/hoertest/ <p>Short guide for non German speakers: ---------------------------------------------------------------------------- stepp 1 browse to: http://www.heise.de/ct/leserbefragung/hoertest/ Down on that page is a link with the name

Hi everyone, Here's a follow-up on the two BoFs we've had about doing royalty-free codecs at the IETF. Well, the good new is that the proposal is now in IETF last call until January 20th (see below). No final decision has been made, so it's important to get as much support as possible for the Working Group proposal. You can see the ongoing discussion on the mailing list archive:

Hi everyone, Here's a follow-up on the two BoFs we've had about doing royalty-free codecs at the IETF. Well, the good new is that the proposal is now in IETF last call until January 20th (see below). No final decision has been made, so it's important to get as much support as possible for the Working Group proposal. You can see the ongoing discussion on the mailing list archive:

Hello List, I have a data frame object (wa2) that I am exporting for use in another statistics package. Using library(foreign) write.foreign(wa2, choose.files(), choose.files(), package='SPSS') I noticed that there were several differences between the data sets as seen within R (View(wa2)) and what was produced in SPSS. Examining the data file produced by write.foreign (before running

Hi R users,I have a question about augmented prediction plot (?augPred). The covariate of my data set is c(0, 0.01, 0.1, 1, 10, 100, 1000) and I have fitted a nonlinear mixed effects model.I use plot(augPred(out.nlme....)) to get the augmented prediction plot. However, because the scale of the covariate is too large thus I am not able to see the detail difference at c(0,0.01, 0.1, and 1). Could

Hi am little novice over your product but also need a good hand reinstalling your server platform under linux servers steppes that where already done uncrompressed the tar.gz file in out of the www.folder so is now home/gysmonet/icecast/ next did run the configure file as said then did tried make make install and seems nothing happening Do i need to cofigure anything before running the