Try this, Pietro ... # example data aaa <- matrix(rnorm(60), ncol=3) bbb <- matrix(runif(15), ncol=3)
# calculate quantiles ccc <- sapply(1:dim(aaa)[2], function(i) quantile(aaa[, i], bbb[, i])) # change rownames rownames(ccc) <- seq(dim(ccc)[1]) Jean On Sat, Jun 8, 2013 at 8:20 AM, Parodi, Pietro <pietro.par...@willis.com>wrote: > Hello > > I have a matrix aaa like this: > > aa1 aa2 aa3 > [1,] 8371.417 27613.57 1170.466 > [2,] 14317.999 42421.82 3423.934 > [3,] 22026.466 59874.14 8103.084 > [4,] 33884.986 84506.34 19176.764 > [5,] 57954.968 129824.30 56097.310 > > where each column represents an empirical distribution of random variates > (normally the number of rows would be, say, 10,000 or 100,000) and a matrix > bbb of percentiles like this: > > bbb > > [,1] [,2] [,3] > [1,] 0.70092980 0.8144194 0.6200732 > [2,] 0.77968803 0.5804948 0.5463661 > [3,] 0.01509415 0.9313509 0.8611973 > [4,] 0.22654757 0.6183386 0.4962867 > [5,] 0.36548835 0.6608696 0.3062784 > What I'd like to do is to apply the quantiles in the three columns of bbb > to the columns of aaa independently, so as to obtain a matrix ccc such > that, for example, ccc[3,1]=quantile(aaa[,1],bbb[3,1]). THe complete matrix > is: > > > ccc = quantile(aaa[,1],bbb[1,1]), quantile(aaa[,2],bbb[1,2]), > quantile(aaa[,3],bbb[1,3]) > quantile(aaa[,1],bbb[2,1]), quantile(aaa[,2],bbb[2,2]), > quantile(aaa[,3],bbb[2,3]) > quantile(aaa[,1],bbb[3,1]), quantile(aaa[,2],bbb[3,2]), > quantile(aaa[,3],bbb[3,3]) > quantile(aaa[,1],bbb[4,1]), quantile(aaa[,2],bbb[4,2]), > quantile(aaa[,3],bbb[4,3]) > quantile(aaa[,1],bbb[5,1]), quantile(aaa[,2],bbb[5,2]), > quantile(aaa[,3],bbb[5,3]) > > > > Now if I only two vectors, it would be enough for me to define > ccc=quantile(aaa,bbb). However, if I do this when aaa and bbb are matrix, > quantile(aaa,bbb) does something else -- it gives the percentiles bbb of > the whole set of matrix elements rather than considering separately the > quantiles of the different columns. > > I suspect I'll need to use "apply" in some form but have been able to come > up with the correct form. > > As you might have imagined, this arises in the context of simulating > random variables from different distribution in empirical form that are > correlated through a copula. > > Thanks in advance for your help! > > Pietro > _ > > ______________________________________________________________________ > > For information pertaining to Willis' email confidentiality and monitoring > policy, usage restrictions, or for specific company registration and > regulatory status information, please visit > http://www.willis.com/email_trailer.aspx > > We are now able to offer our clients an encrypted email capability for > secure communication purposes. If you wish to take advantage of this > service or learn more about it, please let me know or contact your Client > Advocate for full details. ~W67897 > ______________________________________________________________________ > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
