calc_perm_p_value

<code>calc_perm_p_value</code> calculates the permutation p-value following PhiSmy10perm;textualrobnptests.

internal

Implementations of several robust nonparametric two-sample tests
for location or scale differences. The test statistics are based on robust
location and scale estimators, e.g. the sample median or the Hodges-Lehmann estimators
as described in Fried & Dehling (2011) <doi:10.1007/s10260-011-0164-1>.
The p-values can be computed via the permutation principle, the randomization principle, or by using
the asymptotic distributions of the test statistics under the null hypothesis, which ensures
(approximate) distribution independence of the test decision. To test for a difference in
scale, we apply the tests for location difference to transformed observations; see Fried (2012) <doi:10.1016/j.csda.2011.02.012>.
Random noise on a small range can be added to the original observations in order to
hold the significance level on data from discrete distributions.
The location tests assume homoscedasticity and the scale tests require the
location parameters to be zero.

Sermad Abbas

robnptests

Robust Nonparametric Two-Sample Tests for Location/Scale

Barbara Brune

Roland Fried

calc_perm_p_value function

<dl><dt>statistic</dt>
<dd>observed value of the test statistic.</dd>
<dt>distribution</dt>
<dd>a numeric vector with the permutation/randomization
distribution.</dd>
<dt>m</dt>
<dd>an integer value giving size of first sample.</dd>
<dt>n</dt>
<dd>an integer value giving size of second sample.</dd>
<dt>randomization</dt>
<dd>a logical value indicating whether the p-value should be
computed from a permutation (<code>FALSE</code>, default) or a
randomization (<code>TRUE</code>) distribution.</dd>
<dt>n.rep</dt>
<dd>an integer value specifying the number of random splits used to
calculate the randomization distribution if <code>method = "randomization"</code>.
This argument is ignored if <code>method = "permutation"</code> or <code>method = "asymptotic"</code>.
The default is <code>n.rep = 10000</code>.</dd>
<dt>alternative</dt>
<dd>a character string specifying the alternative hypothesis,
must be one of "two.sided" (default), "greater", or "less".</dd></dl>

Arguments

Calculation of permutation p-value — calc_perm_p_value

<dl>

<dt>statistic</dt>
<dd>observed value of the test statistic.</dd>


<dt>distribution</dt>
<dd>a numeric vector with the permutation/randomization
distribution.</dd>


<dt>m</dt>
<dd>an integer value giving size of first sample.</dd>


<dt>n</dt>
<dd>an integer value giving size of second sample.</dd>


<dt>randomization</dt>
<dd>a logical value indicating whether the p-value should be
computed from a permutation (<code>FALSE</code>, default) or a
randomization (<code>TRUE</code>) distribution.</dd>


<dt>n.rep</dt>
<dd>an integer value specifying the number of random splits used to
calculate the randomization distribution if <code>method = "randomization"</code>.
This argument is ignored if <code>method = "permutation"</code> or <code>method = "asymptotic"</code>.
The default is <code>n.rep = 10000</code>.</dd>


<dt>alternative</dt>
<dd>a character string specifying the alternative hypothesis,
must be one of "two.sided" (default), "greater", or "less".</dd>

</dl>

calc_perm_p_value: Calculation of permutation p-value

Description

Usage

Value

Arguments

References