Package: KSgeneral 2.0.2

Dimitrina S. Dimitrova

KSgeneral: Computing P-Values of the One-Sample K-S Test and the Two-Sample K-S and Kuiper Tests for (Dis)Continuous Null Distribution

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.

Authors:Dimitrina S. Dimitrova <[email protected]>, Yun Jia <[email protected]>, Vladimir K. Kaishev <[email protected]>, Senren Tan <[email protected]>

KSgeneral_2.0.2.tar.gz
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KSgeneral.pdf |KSgeneral.html✨
KSgeneral/json (API)

# Install 'KSgeneral' in R:
install.packages('KSgeneral', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/d-dimitrova/ksgeneral/issues

Uses libs:
  • fftw3– Library for computing Fast Fourier Transforms
  • c++– GNU Standard C++ Library v3
Datasets:
  • Population_Data - The proportion of inhabitants living within a 200 kilometer wide costal strip in 232 countries in the year 2010

fftw3cpp

2.11 score 16 scripts 403 downloads 14 exports 3 dependencies

Last updated 4 months agofrom:561412096f. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 27 2024
R-4.5-linux-x86_64OKNov 27 2024

Exports:cont_ks_c_cdfcont_ks_cdfcont_ks_testdisc_ks_c_cdfdisc_ks_testks_c_cdf_RcppKS2sampleKS2sample_c_RcppKS2sample_RcppKuiper2sampleKuiper2sample_c_RcppKuiper2sample_Rcppmixed_ks_c_cdfmixed_ks_test

Dependencies:dgofMASSRcpp

Readme and manuals

Help Manual

Help pageTopics
Computing P-Values of the One-Sample K-S Test and the Two-Sample K-S and Kuiper Tests for (Dis)Continuous Null DistributionKSgeneral-package
Computes the complementary cumulative distribution function of the two-sided Kolmogorov-Smirnov statistic when the cdf under the null hypothesis is continuouscont_ks_c_cdf
Computes the cumulative distribution function of the two-sided Kolmogorov-Smirnov statistic when the cdf under the null hypothesis is continuouscont_ks_cdf
Computes the p-value for a one-sample two-sided Kolmogorov-Smirnov test when the cdf under the null hypothesis is continuouscont_ks_test
Computes the complementary cumulative distribution function of the two-sided Komogorov-Smirnov statistic when the cdf under the null hypothesis is purely discretedisc_ks_c_cdf
Computes the p-value for a one-sample two-sided Kolmogorov-Smirnov test when the cdf under the null hypothesis is purely discretedisc_ks_test
R function calling directly the C++ routines that compute the complementary cumulative distribution function of the two-sided (or one-sided, as a special case) Kolmogorov-Smirnov statistic, when the cdf under the null hypothesis is arbitrary (i.e., purely discrete, mixed or continuous)ks_c_cdf_Rcpp
Computes the p-value for a (weighted) two-sample Kolmogorov-Smirnov test, given an arbitrary positive weight function and arbitrary data samples with possibly repeated observations (i.e. ties)KS2sample
R function calling the C++ routines that compute the complementary p-value for a (weighted) two-sample Kolmogorov-Smirnov (KS) test, given an arbitrary positive weight function and arbitrary data samples with possibly repeated observations (i.e. ties)KS2sample_c_Rcpp
R function calling the C++ routines that compute the p-value for a (weighted) two-sample Kolmogorov-Smirnov (KS) test, given an arbitrary positive weight function and arbitrary data samples with possibly repeated observations (i.e. ties)KS2sample_Rcpp
Computes the p-value for a two-sample Kuiper test, given arbitrary data samples on the real line or on the circle with possibly repeated observations (i.e. ties)Kuiper2sample
R function calling the C++ routines that compute the complementary p-value for a (unweighted) two-sample Kuiper test, given arbitrary data samples on the real line or on the circle with possibly repeated observations (i.e. ties)Kuiper2sample_c_Rcpp
R function calling the C++ routines that compute the p-value for a (unweighted) two-sample Kuiper test, given arbitrary data samples on the real line or on the circle with possibly repeated observations (i.e. ties)Kuiper2sample_Rcpp
Computes the complementary cumulative distribution function of the two-sided Kolmogorov-Smirnov statistic when the cdf under the null hypothesis is mixedmixed_ks_c_cdf
Computes the p-value for a one-sample two-sided Kolmogorov-Smirnov test when the cdf under the null hypothesis is mixedmixed_ks_test
The proportion of inhabitants living within a 200 kilometer wide costal strip in 232 countries in the year 2010Population_Data