plot_power

This function draws the power graph, with curves sorted by the mean power and smoothed for easier reading.

Routines that allow the user to run a large number of goodness-of-fit tests.
It allows for data to be continuous or discrete. It includes routines to estimate
the power of the tests and display them as a power graph.
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

Rgof

1d Goodness of Fit Tests

plot_power function

<dl><dt>pwr</dt>
<dd>a matrix of power values, usually from the twosample_power command</dd>
<dt>xname</dt>
<dd>Name of variable on x axis</dd>
<dt>title</dt>
<dd>(Optional) title of graph</dd>
<dt>Smooth</dt>
<dd>=TRUE lines are smoothed for easier reading</dd>
<dt>span</dt>
<dd>=0.25bandwidth of smoothing method</dd></dl>

Arguments

This function draws the power graph, with curves sorted by the mean power and smoothed for easier reading. — plot_power

<dl>

<dt>pwr</dt>
<dd>a matrix of power values, usually from the twosample_power command</dd>


<dt>xname</dt>
<dd>Name of variable on x axis</dd>


<dt>title</dt>
<dd>(Optional) title of graph</dd>


<dt>Smooth</dt>
<dd>=TRUE lines are smoothed for easier reading</dd>


<dt>span</dt>
<dd>=0.25bandwidth of smoothing method</dd>

</dl>

plot_power: This function draws the power graph, with curves sorted by the mean power and smoothed for easier reading.

Description

Usage

Value

Arguments