ddst: Data Driven Smooth Tests

Smooth tests are data driven (alternative hypothesis is dynamically selected based on data). In this package you will find two groups of smooth of test: goodness-of-fit tests and nonparametric tests for comparing distributions. Among goodness-of-fit tests there are tests for exponent, Gaussian, Gumbel and uniform distribution. Among nonparametric tests there are tests for stochastic dominance, k-sample test, test with umbrella alternatives and test for change-point problems.

Version: 1.6.11
Depends: R (≥ 2.7), polynom
Imports: ggplot2, orthopolynom, evd
Suggests: rmutil, knitr
Published: 2026-09-12
DOI: 10.32614/CRAN.package.ddst
Author: Przemyslaw Biecek ORCID iD [aut, cre], Teresa Ledwina [aut], Grzegorz Wylupek [aut]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek at gmail.com>
BugReports: https://github.com/pbiecek/ddst/issues
License: GPL-2
URL: https://pbiecek.github.io/ddst/
NeedsCompilation: no
Materials: NEWS
CRAN checks: ddst results

Documentation:

Reference manual: ddst.html , ddst.pdf
Vignettes: Examples for ddst package (source, R code)

Downloads:

Package source: ddst_1.6.11.tar.gz
Windows binaries: r-devel: ddst_1.4.zip, r-release: ddst_1.4.zip, r-oldrel: ddst_1.4.zip
macOS binaries: r-release (arm64): ddst_1.4.tgz, r-oldrel (arm64): ddst_1.6.11.tgz, r-release (x86_64): ddst_1.6.11.tgz, r-oldrel (x86_64): ddst_1.6.11.tgz
Old sources: ddst archive

Reverse dependencies:

Reverse depends: GLDreg
Reverse imports: simgof

Linking:

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