Package: KSgeneral
Type: Package
Version: 2.1.0
Title: Computing P-Values of the One-Sample K-S Test and the Two-Sample
        K-S and Kuiper Tests for (Dis)Continuous Null Distribution
Authors@R: c(
    person(given = c("Dimitrina", "S."),
           family = "Dimitrova",
           role = c("aut", "cre"),
           email = "D.Dimitrova@city.ac.uk"),
    person(given = "Yun",
           family = "Jia",
           role = "aut",
           email = "yunjia2019@gmail.com"),
    person(given = c("Vladimir", "K."),
           family = "Kaishev",
           role = "aut",
           email = "Vladimir.Kaishev.1@city.ac.uk"),
    person(given = "Senren",
           family = "Tan",
           role = "aut",
           email = "raymondtsrtsr@outlook.com")
  )
Depends: R (>= 3.3.0)
SystemRequirements: fftw3 (>=3.3.4)
Copyright: Copyright holders of FFTW3: Copyright (c) 2003, 2007-11
        Matteo Frigo; Copyright (c) 2003, 2007-11 Massachusetts
        Institute of Technology
Description: Contains functions to compute p-values for the one-sample
        and two-sample Kolmogorov-Smirnov (KS) tests and the two-sample
        Kuiper test for any fixed critical level and arbitrary
        (possibly very large) sample sizes. For the one-sample KS test,
        this package implements a novel, accurate and efficient method
        named Exact-KS-FFT, which allows the pre-specified cumulative
        distribution function under the null hypothesis to be
        continuous, purely discrete or mixed. In the two-sample case,
        it is assumed that both samples come from an unspecified
        (unknown) continuous, purely discrete or mixed distribution,
        i.e. ties (repeated observations) are allowed, and exact
        p-values of the KS and the Kuiper tests are computed. Note, the
        two-sample Kuiper test is often used when data samples are on
        the line or on the circle (circular data). To cite this package
        in publication: (for the use of the one-sample KS test)
        Dimitrina S. Dimitrova, Vladimir K. Kaishev, and Senren Tan.
        Computing the Kolmogorov-Smirnov Distribution When the
        Underlying CDF is Purely Discrete, Mixed, or Continuous.
        Journal of Statistical Software. 2020; 95(10): 1--42.
        <doi:10.18637/jss.v095.i10>. (for the use of the two-sample KS
        and Kuiper tests) Dimitrina S. Dimitrova, Yun Jia and Vladimir
        K. Kaishev (2024). The R functions KS2sample and Kuiper2sample:
        Efficient Exact Calculation of P-values of the Two-sample
        Kolmogorov-Smirnov and Kuiper Tests. submitted.
License: GPL (>= 2.0)
URL: https://github.com/d-dimitrova/KSgeneral
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.12), MASS, dgof
LinkingTo: Rcpp
NeedsCompilation: yes
Config/pak/sysreqs: libfftw3-dev
Repository: https://d-dimitrova.r-universe.dev
Date/Publication: 2026-10-02 21:25:02 UTC
RemoteUrl: https://github.com/d-dimitrova/ksgeneral
RemoteRef: HEAD
RemoteSha: 7a2acf5bbaae10c7865cbc8c136fa5dd4151d821
Packaged: 2026-10-02 23:46:34 UTC; root
Author: Dimitrina S. Dimitrova [aut, cre],
  Yun Jia [aut],
  Vladimir K. Kaishev [aut],
  Senren Tan [aut]
Maintainer: Dimitrina S. Dimitrova <D.Dimitrova@city.ac.uk>