Is this what you are looking for? newrec <- rep(recoveries[,1], recoveries[,2]) plot(density(newrec), ylim=c(0, 5)) lines(density(newrec*.67), col="red") plot(ecdf(newrec), xlim=c(0,1), verticals=TRUE) lines(ecdf(newrec*.67), verticals=TRUE, col="red")
---------------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77843-4352 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of Keith Weintraub > Sent: Tuesday, June 19, 2012 11:00 AM > To: Bert Gunter > Cc: r-help@r-project.org > Subject: Re: [R] Scaling a "density". > > Bert, > Thanks for your help and comments. > > My inferior writing skills have failed to elucidate what I thought were > implicit questions in the following: > > I would like to plot this: > > > recoveries*matrix(c(.67,1),nrow = 11, ncol = 2, byrow = TRUE) > pcts counts > [1,] 0.000 0 > [2,] 0.067 0 > [3,] 0.134 0 > [4,] 0.201 0 > [5,] 0.268 0 > [6,] 0.335 4 > [7,] 0.402 0 > [8,] 0.469 1 > [9,] 0.536 2 > [10,] 0.603 2 > [11,] 0.670 12 > > using densityplot or an equivalent but on the original scale with pcts > going from 0.0 to 1.0. Can someone give me an example or pointer to > complete this task? > > In addition I would like to either "integrate" the density plot or > come up with a smooth version of the CDF after the 67% contraction. How > would I go about doing this? > > In regards to your second point we are not looking to draw deep > inferences, just a reasonable looking graph for a presentation to go > along with the data table. Some folks just like to see pretty pictures. > > Thanks so much for your time, > KW > > > -- > > On Jun 19, 2012, at 11:37 AM, Bert Gunter wrote: > > > 1. You have not asked a question. > > > > 2. Your data set is too small to do anything more with it than show > it in a table as you have done. (IMHO) anything more than that would be > wild, foolish, unsupportable, and misleading "statisticizing" -- by > which I mean creating the appearance of having more and more precise > information than you actually have by employing complex (if possible) > statistical methods. * > > > > -- Bert > > > > * A common practice in many scientific fields these days, I admit. > One would hope that practical arenas like yours would avoid this, > however. > > > > > > > > On Tue, Jun 19, 2012 at 8:22 AM, Keith Weintraub <kw1...@gmail.com> > wrote: > > Folks, > > I have a small dataset of counts of recoveries on defaulted loans: > > > > recoveries<-structure(c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, > 0.9, 1, > > 0, 0, 0, 0, 0, 4, 0, 1, 2, 2, 12), .Dim = c(11L, 2L), .Dimnames = > list( > > NULL, c("pcts", "counts"))) > > > > Here is the data in columnar form: > > pcts counts > > [1,] 0.0 0 > > [2,] 0.1 0 > > [3,] 0.2 0 > > [4,] 0.3 0 > > [5,] 0.4 0 > > [6,] 0.5 4 > > [7,] 0.6 0 > > [8,] 0.7 1 > > [9,] 0.8 2 > > [10,] 0.9 2 > > [11,] 1.0 12 > > > > For example row [6,] means that in our historical sample we saw 50% > recoveries 4 times. > > > > Now I would like to "stress" the recovery distribution by say 67% so > that the counts would stay the same but the bins (pcts) would contract > like so: > > > > > recoveries*matrix(c(.67,1),nrow = 11, ncol = 2, byrow = TRUE) > > pcts counts > > [1,] 0.000 0 > > [2,] 0.067 0 > > [3,] 0.134 0 > > [4,] 0.201 0 > > [5,] 0.268 0 > > [6,] 0.335 4 > > [7,] 0.402 0 > > [8,] 0.469 1 > > [9,] 0.536 2 > > [10,] 0.603 2 > > [11,] 0.670 12 > > > > I would like to plot this using densityplot or an equivalent but on > the original scale from 0.0 to 1.0. > > > > In addition I would like to either "integrate" the density plot or > come up with a smooth version of the CDF after the 67% contraction. > > > > I hope this is clear, > > Thanks for your time, > > KW > > > > > > > > -- > > > > > > [[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. > > > > > > > > -- > > > > Bert Gunter > > Genentech Nonclinical Biostatistics > > > > Internal Contact Info: > > Phone: 467-7374 > > Website: > > http://pharmadevelopment.roche.com/index/pdb/pdb-functional- > groups/pdb-biostatistics/pdb-ncb-home.htm > > > > > > > [[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. ______________________________________________ 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.