Dear Kjetil, As I already mentioned, it appears that there isn't a function available calculating the quantiles directly (at least, it doesn't appear in the C source of ctest). So as I already suggested, uniroot (or a similar C routine which calls the corresponding C code directly) is probably the best you can do (apart from writing it completely yourself).
I didn't program this using uniroot, but I'd certainly try the following for speed-up: - For symmetry reasons, you only need to compute half of the quantiles. - The quantiles depend smoothly on the probabilities (of your reference distribution). Therefore, calculating only a "few" for probabilities between 0 and 0.5, and using (e.g. linear) interpolation should be satisfying. I am sorry not be of more help. HTH anyway Thomas > -----Original Message----- > From: kjetil brinchmann halvorsen [mailto:[EMAIL PROTECTED] > Sent: 23 July 2003 15:46 > To: Hotz, T. > Subject: RE: [R] Confidence Band for empirical distribution function > > > On 22 Jul 2003 at 11:37, Hotz, T. wrote: > > > Dear Leif, > > > > If you look at the definition of ks.test, you'll find the lines > > > > pkstwo <- function(x, tol = 1e-06) { > > if (is.numeric(x)) > > x <- as.vector(x) > > else stop("Argument x must be numeric") > > p <- rep(0, length(x)) > > p[is.na(x)] <- NA > > IND <- which(!is.na(x) & (x > 0)) > > if (length(IND) > 0) { > > p[IND] <- .C("pkstwo", as.integer(length(x)), p = > as.double(x[IND]), > > as.double(tol), PACKAGE = "ctest")$p > > } > > return(p) > > } > > > > which calls C code to calculate the p-values given the test > statistic. > > You'll find explanations on what this function does in the > original C file > > src/library/ctest/src/ks.c > > > > I haven't tried that but I assume that you could use it to > calculate p-values > > given the test-statistics yourself. > > That could certainly be done, but what was asked for is the inverse, > which can be calculated, using for instance uniroot(). I tried that, > but it is to slow, .C() will be called repeatedly in a loop. For me > it took several minutes. > > Kjetil Halvorsen > > > > > Please also note that ks.test() returns the p-value as well. > > > > If you need quantiles, I assume you need to invert the cdf yourself, > > e.g. using uniroot(). > > > > HTH > > > > Thomas > > > > --- > > > > Thomas Hotz > > Research Associate in Medical Statistics > > University of Leicester > > United Kingdom > > > > Department of Epidemiology and Public Health > > 22-28 Princess Road West > > Leicester > > LE1 6TP > > Tel +44 116 252-5410 > > Fax +44 116 252-5423 > > > > Division of Medicine for the Elderly > > Department of Medicine > > The Glenfield Hospital > > Leicester > > LE3 9QP > > Tel +44 116 256-3643 > > Fax +44 116 232-2976 > > > > > > > -----Original Message----- > > > From: Leif.Boysen [mailto:[EMAIL PROTECTED] > > > Sent: 21 July 2003 14:42 > > > To: [EMAIL PROTECTED] > > > Subject: [R] Confidence Band for empirical distribution function > > > > > > > > > Hi, > > > > > > I was trying to draw an empirical distribution function > with uniform > > > confidence bands. So I tried to find a way to calculate > values of the > > > Kolmogorov-Smirnov Distribution but failed. > > > I guess it must be hidden somewhere (since the ks-test is > > > implemented), > > > but I was unable to find it. > > > > > > Is there any way to do this? > > > > > > Thanks > > > > > > Leif Boysen > > > > > > ______________________________________________ > > > [EMAIL PROTECTED] mailing list > > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > > > > ______________________________________________ > > [EMAIL PROTECTED] mailing list > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help