plot.twosamples

Typically for now this will produce a histogram of the
null distribution based on the bootstrapped values,
with a vertical line marking the value of the test statistic.

Fast randomization based two sample tests.
Testing the hypothesis that two samples come from the same distribution using randomization to create p-values. Included tests are: Kolmogorov-Smirnov, Kuiper, Cramer-von Mises, Anderson-Darling, Wasserstein, and DTS. The default test (two_sample) is based on the DTS test statistic, as it is the most powerful, and thus most useful to most users.
The DTS test statistic builds on the Wasserstein distance by using a weighting scheme like that of Anderson-Darling. See the companion paper at <arXiv:2007.01360> or <https://codowd.com/public/DTS.pdf> for details of that test statistic, and non-standard uses of the package (parallel for big N, weighted observations, one sample tests, etc). We also include the permutation scheme to make test building simple for others.

Connor Dowd

twosamples

Fast Permutation Based Two Sample Tests

plot.twosamples function

<dl><dt>x</dt>
<dd>an object produced by one of the twosamples <code>*_test</code> functions</dd>
<dt>plot_type</dt>
<dd>which plot to create? only current option is "boots_hist",</dd>
<dt>nbins</dt>
<dd>how many bins (or breaks) in the histogram</dd>
<dt>...</dt>
<dd>other parameters to be passed to plotting functions</dd></dl>

Arguments

Default plots for twosamples objects — plot.twosamples

<dl>

<dt>x</dt>
<dd>an object produced by one of the twosamples <code>*_test</code> functions</dd>


<dt>plot_type</dt>
<dd>which plot to create? only current option is "boots_hist",</dd>


<dt>nbins</dt>
<dd>how many bins (or breaks) in the histogram</dd>


<dt>...</dt>
<dd>other parameters to be passed to plotting functions</dd>

</dl>

plot.twosamples: Default plots for `twosamples` objects

Description

Usage

Value

Arguments

See Also

Examples