This plot function takes a univariate sample that should be tested for
a U(0,1) distribution, plots its empirical cumulative distribution
ecdf), and adds a confidence band by inverting
the corresponding Kolmogorov-Smirnov test (
uniform distribution is rejected if the ECDF is not completely inside
the confidence band.
ks.plot.unif(U, conf.level = 0.95, exact = NULL, col.conf = "gray", col.ref = "gray", xlab = expression(u[(i)]), ylab = "Cumulative distribution")
numeric vector containing the sample. Missing values are (silently) ignored.
confidence level for the K-S-test (defaults to 0.95), can also be a vector of multiple levels.
colour of the confidence lines.
colour of the diagonal reference line.
Michael Höhle and Sebastian Meyer.
The code contains segments originating from the source of the ks.test function
which is Copyright (C) 1995-2012 The R Core Team available under GPL-2
(or later) and C functionality from
which is copyright (C) 1999-2009 the R Core Team and available under
GPL-2 (or later). Somewhat hidden in their
ks.c file is a statement
that part of their code is based on code published in
Marsaglia et al. (2003).
George Marsaglia and Wai Wan Tsang and Jingbo Wang (2003): Evaluating Kolmogorov's distribution. Journal of Statistical Software, 8 (18). doi: 10.18637/jss.v008.i18