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ddst (version 1.6.11)

Data Driven Smooth Tests

Description

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.

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Version

Install

install.packages('ddst')

Monthly Downloads

220

Version

1.6.11

License

GPL-2

Maintainer

Przemyslaw Biecek

Last Published

September 12th, 2026

Functions in ddst (1.6.11)

ddst.twosample.test

Data Driven Smooth Test for Two-Sample Problem
plot.ddst.test

Plot Function fo Data Driven Tests
ddst.umbrellaknownp.test

Data Driven Smooth Test for Umbrella Alternatives; Known Peak
ddst.normbounded.test

Data Driven Smooth Test for Normality; Bounded Basis Functions
ddst.forstochdom.test

Data Driven Smooth Test for Stochastic Dominance in Two Samples
ddst.againststochdom.test

Data Driven Smooth Test Against Stochastic Dominance
ddst.upwardtrend.test

Data Driven Smooth Test for Upward Trend Alternatives
ddst.exp.test

Data Driven Smooth Test for Exponentiality
ddst.normubounded.test

Data Driven Smooth Test for Normality; Unbounded Basis Functions
ddst.evd.test

Data Driven Smooth Test for Extreme Value Distribution
ddst.ksample.test

Data Driven Smooth Test for k-Sample Problem
ddst.umbrellaunknownp.test

Data Driven Smooth Test for Umbrella Alternatives; Unknown Peak
ddst.uniform.test

Data Driven Smooth Test for Uniformity