ks.plot.unif {surveillance}

Plot the ECDF of a uniform sample with Kolmogorov-Smirnov bounds

Description

This plot function takes a univariate sample that should be tested for a U(0,1) distribution, plots its empirical cumulative distribution function (ecdf), and adds a confidence band by inverting the corresponding Kolmogorov-Smirnov test (ks.test). The uniform distribution is rejected if the ECDF is not completely inside the confidence band.

Usage

ks.plot.unif(U, conf.level = 0.95, exact = NULL,
             col.conf = "gray", col.ref = "gray",
             xlab = expression(u[(i)]), ylab = "Cumulative distribution")

Arguments

U

numeric vector containing the sample. Missing values are (silently) ignored.

conf.level

confidence level for the K-S-test (defaults to 0.95), can also be a vector of multiple levels.

exact

see ks.test.

col.conf

colour of the confidence lines.

col.ref

colour of the diagonal reference line.

xlab, ylab

axis labels.

Value

NULL (invisibly).

Author(s)

Michael Höhle and Sebastian Meyer.

The code re-uses fragments from the ks.test source file https://svn.R-project.org/R/trunk/src/library/stats/R/ks.test.R, with Copyright (C) 1995-2022 The R Core Team, available under GPL-2 (or later), and C functionality from the source file https://svn.R-project.org/R/trunk/src/library/stats/src/ks.c, partially based on code published in Marsaglia et al. (2003), with Copyright (C) 1999-2022 The R Core Team, also available under GPL-2 (or later).

References

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

See Also

ks.test for the Kolmogorov-Smirnov test, as well as checkResidualProcess, which makes use of this plot function.

Examples

samp <- runif(99)
ks.plot.unif(samp, conf.level=c(0.95, 0.99), exact=TRUE)
ks.plot.unif(samp, conf.level=c(0.95, 0.99), exact=FALSE)