Feedstock license: BSD-3-Clause
Home: https://CRAN.R-project.org/package=dunn.test
Package license: GPL-2.0-only
Summary: Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.
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Installing r-dunn.test from the conda-forge channel can be achieved by adding conda-forge to your channels with:
conda config --add channels conda-forge
conda config --set channel_priority strict
Once the conda-forge channel has been enabled, r-dunn.test can be installed with conda:
conda install r-dunn.test
or with mamba:
mamba install r-dunn.test
It is possible to list all of the versions of r-dunn.test available on your platform with conda:
conda search r-dunn.test --channel conda-forge
or with mamba:
mamba search r-dunn.test --channel conda-forge
Alternatively, mamba repoquery may provide more information:
# Search all versions available on your platform:
mamba repoquery search r-dunn.test --channel conda-forge
# List packages depending on `r-dunn.test`:
mamba repoquery whoneeds r-dunn.test --channel conda-forge
# List dependencies of `r-dunn.test`:
mamba repoquery depends r-dunn.test --channel conda-forge
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If you would like to improve the r-dunn.test recipe or build a new
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- If the version of a package is not being increased, please add or increase
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build/numberback to 0.