search for: kuantile

...evel Version 2.3.0 Under development > (unstable) (2006-03-12 r37524) > on a G5 and things went smoothly despite my gfortran configuration, > (that is ./configure, make, > make install was fine), but now trying to install a source package > I get: > > yzzy: R CMD check kuantile > * checking for working latex ... OK > * using log directory '/Users/roger/Projects/kuantile/kuantile.Rcheck' > * using Version 2.3.0 Under development (unstable) (2006-03-12 r37524) > * checking for file 'kuantile/DESCRIPTION' ... OK > * this is package 'kuantil...

...iwiel: On Floyd and Rivest's SELECT Algorithm, Theoretical Computer Sci. 347 (2005) 214-238. He has also kindly agreed to allow me to incorporate his implementation of the FR algorithm in R under GPL. For the moment, I have made an alpha-test package with a single function -- 'kuantile' -- that attempts to reproduce the functionality of the current base quantile function, essentially replacing the partial sorting done there with calls to Kiwiel's 'select' function. This package is available from: http://www.econ.uiuc.edu/~roger/research/rq/kuantile...

Hi, I've got two suggestions how to speed up median() about 50%. For all iterative methods calling median() in the loops this has a major impact. The second suggestion will apply to other methods too. This is what the functions look like today: > median function (x, na.rm = FALSE) { if (is.factor(x) || mode(x) != "numeric") stop("need numeric data")

Does any have installation instructions for this? When I run install.packages('quantreg') I get: gcc -std=gnu99 -shared -o quantreg.so akj.o boot.o brute.o chlfct.o cholesky.o combos.o crq.o crqfnb.o dsel05.o etime.o extract.o idmin.o iswap.o kuantile.o mcmb.o penalty.o powell.o rls.o rq0.o rq1.o rqbr.o rqfn.o rqfnb.o rqfnc.o sparskit2.o srqfn.o srqfnc.o srtpai.o -llapack -lblas -lgfortran -lm -lgfortran -lm -L/usr/lib/R/lib -lR /usr/bin/ld: cannot find -llapack > sessionInfo() R version 2.9.0 (2009-04-17) i486-pc-linux-gnu locale: LC_C...

...-c crqfnb.f -o crqfnb.o gfortran -fpic -g -O2 -c dsel05.f -o dsel05.o gfortran -fpic -g -O2 -c etime.f -o etime.o gfortran -fpic -g -O2 -c extract.f -o extract.o gfortran -fpic -g -O2 -c idmin.f -o idmin.o gfortran -fpic -g -O2 -c iswap.f -o iswap.o gfortran -fpic -g -O2 -c kuantile.f -o kuantile.o gcc -std=gnu99 -I/tools/cluster/6.2/R/3.2.2_mkl/lib64/R/include -I/usr/local/include -fpic -I/panfs/pfs.acf.ku.edu/cluster/system/pkg/R/curl7.45_install/include -L/panfs/pfs.acf.ku.edu/cluster/6.2/R/3.2.2_mkl/lib64 -c mcmb.c -o mcmb.o gfortran -fpic -g -O2 -c penalty.f -o pe...

...-c crqfnb.f -o crqfnb.o gfortran -fpic -g -O2 -c dsel05.f -o dsel05.o gfortran -fpic -g -O2 -c etime.f -o etime.o gfortran -fpic -g -O2 -c extract.f -o extract.o gfortran -fpic -g -O2 -c idmin.f -o idmin.o gfortran -fpic -g -O2 -c iswap.f -o iswap.o gfortran -fpic -g -O2 -c kuantile.f -o kuantile.o gcc -std=gnu99 -I/tools/cluster/6.2/R/3.2.2_mkl/lib64/R/include -I/usr/local/include -fpic -I/panfs/pfs.acf.ku.edu/cluster/system/pkg/R/curl7.45_install/include -L/panfs/pfs.acf.ku.edu/cluster/6.2/R/3.2.2_mkl/lib64 -c mcmb.c -o mcmb.o gfortran -fpic -g -O2 -c penalty.f -o pe...

Hi, I was wondering whether there is any Fortran function or associated library for evaluating the quantiles of a set of values (something which the R-function quantile() does). Any help will be much appreciated. Thanks and regards, Dhiman Bhadra [[alternative HTML version deleted]]

...stance by using only the data between 0.1 and 0.9 quantiles. I cannot use ecdf in this case as my sample is not a whole sample. Therefore I would like to modify the function ecdf as it gives the ecdf between 0.1 and 0.9 quantiles. I wrote ecdf1<- function (x) { x <- sort(x) k<-kuantile(x,c(0.1,0.9)) z<-x[x<=k[2]] z<-z[z>=k[1]] n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- unique(z) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method = &qu...

Hi there, I got a data frame with more than 200k columns. How could I get median of each column fast? mapply is the fastest function I know for that, it's not yet satisfied though. It seems function "median" in R calculates median by "sort" and "mean". I am wondering if there is another function with better algorithm. Any hint? Thanks, Xin Zheng

Hi, This is essentially a reposting of http://tolstoy.newcastle.edu.au/R/devel/05/11/3305.html which had no responses, and the behaviour reported there persists in r-devel as of yesterday. (1) sort() with non-null partial > x = rnorm(100000) > keep = as.integer(ppoints(10000) * 100000) > system.time(sort(x)) [1] 0.05 0.00 0.04 0.00 0.00 > system.time(sort(x, partial = keep)) [1]

Hi group, I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R? Thank u so much 4 ur time. [[alternative HTML version deleted]]