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]]
>
> ______________________________________________
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> PLEASE do read the posting guide
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> 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
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