Gerhard: Strictly speaking, it's quantiles of a custom "distribution", not function.
There may be some way to handle your example easily, but, in general, you would need to solve the resulting integral equation. This is hard -- closed form solutions rarely exist; good approximations require work. So a standard approach is: simulate. Indeed, many simulation tricks (under the rubric of "variance reduction") have been developed exactly for such monte carlo integration. Consult a good reference or knowledgeable person for details. -- Bert On Tue, Jan 3, 2012 at 4:24 AM, Gerhard <felds...@gmx.net> wrote: > Hi, > > I guess that my problem has an obvious answer, but I have not been able to > find it. > > Suppose I create a custom function, consisting of two beta-distributions: > > myfunction <- function(x) { > dbeta(x,2,6) + dbeta(x,6,2) > } > > How can I calculate the quantiles of myfunction? > > I have not seen any continous function treated in the docs, and applying the > "quantile function" gives me an error (since it seems only to be defined on > lists and atoms). > > Thank you in advance, > > Gerhard > > ______________________________________________ > 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 ______________________________________________ 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.