chi_power

This function runs the chi-square test for continuous or discrete data

The routine twosample_test() in this package runs the
two sample test using various test statistic. The p values are
found via permutation or large sample theory. The routine twosample_power() allows the
calculation of the power in various cases, and plot_power() draws the corresponding power graphs.
The routine run.studies allows a user to quickly study the power of a new method and
how it compares to some of the standard ones.

Wolfgang Rolke

R2sample

Various Methods for the Two Sample Problem

chi_power function

<dl><dt>rxy</dt>
<dd>a function to generate data</dd>
<dt>alpha</dt>
<dd>=0.05 type I error probability of test</dd>
<dt>B</dt>
<dd>=1000 number of simulation runs</dd>
<dt>xparam</dt>
<dd>vector of parameter values</dd>
<dt>yparam</dt>
<dd>vector of parameter values</dd>
<dt>nbins</dt>
<dd>=c(50, 10) number of desired bins</dd>
<dt>minexpcount</dt>
<dd>=5 smallest number of counts required in each bin</dd>
<dt>typeTS</dt>
<dd>type of problem, continuous/discrete, with/without weights</dd></dl>

Arguments

This function runs the chi-square test for continuous or discrete data — chi_power

<dl>

<dt>rxy</dt>
<dd>a function to generate data</dd>


<dt>alpha</dt>
<dd>=0.05 type I error probability of test</dd>


<dt>B</dt>
<dd>=1000 number of simulation runs</dd>


<dt>xparam</dt>
<dd>vector of parameter values</dd>


<dt>yparam</dt>
<dd>vector of parameter values</dd>


<dt>nbins</dt>
<dd>=c(50, 10) number of desired bins</dd>


<dt>minexpcount</dt>
<dd>=5 smallest number of counts required in each bin</dd>


<dt>typeTS</dt>
<dd>type of problem, continuous/discrete, with/without weights</dd>

</dl>

chi_power: This function runs the chi-square test for continuous or discrete data

Description

Usage

Value

Arguments