similar to: Trivial formatting typo in summary(lm()) (PR#10480)

Hi, and thanks in advance for your time. Background - I am working on a package and wish to have a routine's progress reported. The routine can take some time, and I would like to inform the user about the routine's progress. I have scoured the archives but to no avail, so would like to solicit input from this list. I am successfully using cat("\rBootstrap replication ", i,

Dear R users, I have a problem for which my objective function depends on both discrete and continuous arguments. The problem is that the number of combinations for the (multivariate) discrete arguments can become overwhelming (when it is univariate this is not an issue) hence search over the continuous arguments for each possible combination of the discrete arguments may not be feasible. Guided

Greetings. For R gurus this may be a no brainer, but I could not find pointers to efficient computation of this beast in past help files. Background - I wish to implement a Cramer-von Mises type test statistic which involves double sums of max(X_i,Y_j) where X and Y are vectors of differing length. I am currently using ifelse pointwise in a vector, but have a nagging suspicion that there is a

Hi. Background - I am working with a dataset involving around 750K observations, where many of the variables (8/11) are unordered factors. The typical model used to model this relationship in the literature has been a simple linear additive model, but this is rejected out of hand by the data. I was asked to model this via kernel methods, but first wanted to play with the parametric

Hi. I am currently running 6.0 (here is uname -a). FreeBSD pc-racine1.mcmaster.ca 6.0-RELEASE-p2 FreeBSD 6.0-RELEASE-p2 #7: Thu Jan 12 09:30:38 EST 2006 root@pc-racine1.mcmaster.ca:/usr/obj/usr/src/sys/OPTIPLEX i386 Just tried a fresh cvsup from cvsup9, a standard compile via cvsup -g -L 2 /usr/share/examples/cvsup/current-supfile && cd /usr/obj && chflags -R noschg *

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

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

Hi, I am about to write functions for multivariate kernel densitiy estimation with mixed categorical and continuous date (accoring to Jeff Racine and Qi Li), and the leave-one-out window esitmation needs a lot of computation. I am now optimizing the code performance and therefore fhe following questions: As R uses call-by-value for functions, is it computational expensive to pass large matrices

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

I can't find any R roadmap. Is it available somewhere ? Etienne -- View this message in context: http://www.nabble.com/Roadmap---tp21791647p21791647.html Sent from the R devel mailing list archive at Nabble.com.

I would like to get the name of the user form the system. Is it possible ? Something like >system.user() returning something like [1] "etber12" Thanks, Etienne [[alternative HTML version deleted]]

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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, With two data sets, one complete and another one partial, I would like to merge them and keep the unmatched lines. The problem is that merge() dosen't keep the unmatched lines. Is there another function that I could use to merge the data frames. Example: completedf <- expand.grid(alpha=letters[1:3],beta=1:3) partdf <- data.frame( alpha= c('a','a','c'),

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