return_mc

S3 class <code>mc</code> object generating function

internal

An implementation of the Monte Carlo techniques described in details by Dufour (2006) <doi:10.1016/j.jeconom.2005.06.007> and Dufour and Khalaf (2007) <doi:10.1002/9780470996249.ch24>. The two main features available are the Monte Carlo method with tie-breaker, mc(), for discrete statistics, and the Maximized Monte Carlo, mmc(), for statistics with nuisance parameters.

Gabriel Rodriguez Rondon

MaxMC

Maximized Monte Carlo

Julien Neves

Jean-Marie Dufour

Gabriel Rodriguez-Rondon

return_mc function

<dl><dt>S0</dt>
<dd>An atomic vector. Value of the test statistic
applied to the data.</dd>
<dt>y</dt>
<dd>A vector or data frame.</dd>
<dt>statistic</dt>
<dd>A function or a character string that specifies
how the statistic is computed. The function needs to input the
<code>y</code> and output a scalar.</dd>
<dt>dgp</dt>
<dd>A function. The function inputs the first argument
<code>y</code> and outputs a simulated <code>y</code>. It should represent the
data generating process under the null. Default value is the function
<code>sample(y, replace = TRUE)</code>, i.e. the
bootstrap resampling of <code>y</code>.</dd>
<dt>N</dt>
<dd>An atomic vector. Number of replications of the test
statistic.</dd>
<dt>type</dt>
<dd>A character string. It specifies the type of test
the p-value function produces. The possible values are
<code>geq</code>, <code>leq</code>, <code>absolute</code> and <code>two-tailed</code>.
 Default is <code>geq</code>.</dd>
<dt>call</dt>
<dd>An object of class <code>call</code>. Original call to <code>mmc</code></dd>
<dt>seed</dt>
<dd>An integer vector. Value of <code>.Random.seed</code> at the start of
<code>mmc</code> call.</dd>
<dt>pval</dt>
<dd>An atomic vector. Monte Carlo p-value of <code>statistic</code></dd></dl>

Arguments

S3 class mc object generating function — return_mc

<dl>

<dt>S0</dt>
<dd>An atomic vector. Value of the test statistic
applied to the data.</dd>


<dt>y</dt>
<dd>A vector or data frame.</dd>


<dt>statistic</dt>
<dd>A function or a character string that specifies
how the statistic is computed. The function needs to input the
<code>y</code> and output a scalar.</dd>


<dt>dgp</dt>
<dd>A function. The function inputs the first argument
<code>y</code> and outputs a simulated <code>y</code>. It should represent the
data generating process under the null. Default value is the function
<code>sample(y, replace = TRUE)</code>, i.e. the
bootstrap resampling of <code>y</code>.</dd>


<dt>N</dt>
<dd>An atomic vector. Number of replications of the test
statistic.</dd>


<dt>type</dt>
<dd>A character string. It specifies the type of test
the p-value function produces. The possible values are
<code>geq</code>, <code>leq</code>, <code>absolute</code> and <code>two-tailed</code>.
 Default is <code>geq</code>.</dd>


<dt>call</dt>
<dd>An object of class <code>call</code>. Original call to <code>mmc</code></dd>


<dt>seed</dt>
<dd>An integer vector. Value of <code>.Random.seed</code> at the start of
<code>mmc</code> call.</dd>


<dt>pval</dt>
<dd>An atomic vector. Monte Carlo p-value of <code>statistic</code></dd>

</dl>

return_mc: S3 class `mc` object generating function

Description

Usage

Arguments