similar to: Versions 0.50-1 of the np and npRmpi packages released - new features and deprecated options…

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

Hi List, I'm using npRmpi to run some density equality tests and place the output into a matrix. I've put together some crude functions for the purpose, but I'm receiving the following error when npdeneqtest() reached the bootstrap; FATAL ERROR: Memory allocation failure (type DBL_VECTOR). Program terminated. I'm running Ubuntu Lucid 64bit with 4 cores and 12GB of memory. My R

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 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, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

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,

Dear all, I have a large dataset of randomly generated weighed sample for which I wish to compute a kernel density estimate. I have used the "np" package successfully for smaller datasets, however for the larger ones, they take too long when using the cross validation options for bandwidth selection ("cv.ls" or "cv.ml"). Of course, they are much quicker with

Dear I have been trying to a program which requires "nprmpi". However, I have tried to install the downloaded zip file but get the error: "cannot open compressed file ''npRmpi_0.40-7.tar.gz/DESCRIPTION''" I tried the command: install.packages("nprmpi") but get the message "package ''nprmpi'' is not available" I then

Hi all, I want to use the npudens() function in the np package (multivariate kernel density estimation), but was confused by the several functions in the following codes,expand.grid(),array(),image() and npudensbw(). This confusion will only be generated in >=3 dimensions. I marked the four places with confusion1-4. I think there should be some kind of correspondence in those four

Dear R users, Version 0.30-6 of the np package has been uploaded to CRAN. See http://cran.r-project.org/package=np Note that the cubature package is now required in addition to the boot package. The recent updates in 0.30-4 through 0.30-6 provides additional functionality in the form of five new functions that incorporate frequently requested nonparametric entropy-based testing methods to the

Dear R users, Version 0.30-6 of the np package has been uploaded to CRAN. See http://cran.r-project.org/package=np Note that the cubature package is now required in addition to the boot package. The recent updates in 0.30-4 through 0.30-6 provides additional functionality in the form of five new functions that incorporate frequently requested nonparametric entropy-based testing methods to the

Hi, I am looking for some help concerning the npudens function in the np package. I am trying to find a kernel density function of a multivariate dataset and the density evaluated at each of the 176 points. I have 2 continuous and 3 ordered discrete variables. My sample size is 176. So edata is a 176x(2+3) data frame, while tdat is a 1x(2+3) vector. bw_cx[i,] is a 1x (2+3) vector

Hi all, I've been trying to run a model using R2winBUGS, and recurrently I get the message: "Error in FUN(X[[3L]], ...) : invalid to change the storage mode of a factor" My model is the following: sink("GLMM_Poisson.txt") cat(" model{ mu~dnorm(0,0.01) beta1~dnorm(-1,1) for(j in 1:nsite){ alpha[j]~dnorm(mu.alpha,tau.alpha) } mu.alpha~dnorm(0,0.01)

Dear R-users, I am fitting a kernel regression model of the form y ~ x1 + factor(x2) + factor(x3) and am using the function npregbw in the np-package to find the optimal bandwidths. My dataset is relatively large and the optimization takes quite long. When testing different specifications I have noticed that the optimal bw for x3 is always very close to zero (around 10^-12 or so). I am

Dear R gurus, I use R all the time at work, so one day a problem managing my personal arise data made me think: "Why not use R, it does everything!". Anyway, my goal is to use R to manage my personal music library, and more precisely my playcounts. I have two XML files, one from Winamp and the other one from Itunes. Both have pretty much the same songs, but their playcounts are