Sampler1DCateg

Sampling from a discrete distribution, for a <a rd-options="" href="/link/ParamFct?package=paradox&version=0.2.0" data-mini-rdoc="paradox::ParamFct">ParamFct</a> or <a rd-options="" href="/link/ParamLgl?package=paradox&version=0.2.0" data-mini-rdoc="paradox::ParamLgl">ParamLgl</a>.

Define parameter spaces, constraints and
dependencies for arbitrary algorithms, to program on such spaces. Also
includes statistical designs and random samplers. Objects are
implemented as 'R6' classes.

Michel Lang

paradox

Define and Work with Parameter Spaces for Complex Algorithms

Bernd Bischl

Jakob Richter

Xudong Sun

Martin Binder

Sampler1DCateg function

<a rd-options="R6:R6Class" href="/link/R6%3A%3AR6Class?package=paradox&version=0.2.0&to=R6%3AR6Class" data-mini-rdoc="R6:R6Class::R6::R6Class">R6::R6Class</a> inheriting from <a rd-options="" href="/link/Sampler1D?package=paradox&version=0.2.0" data-mini-rdoc="paradox::Sampler1D">Sampler1D</a>.

Format

<pre>smpl = Sampler1DCateg$new(param, prob = NULL)
</pre>
<ul>
<li><code>param</code> :: <a rd-options="" href="/link/Param?package=paradox&version=0.2.0" data-mini-rdoc="paradox::Param">Param</a>
Domain / support of the distribution we want to sample from.</li>
<li><code>prob</code> :: <code>numeric()</code>
Numeric vector of <code>param$nlevels</code> probabilities, which is uniform by default.</li>
</ul>

Construction

See <a rd-options="" href="/link/Sampler1D?package=paradox&version=0.2.0" data-mini-rdoc="paradox::Sampler1D">Sampler1D</a>.
Additionally, the class provides:<ul>
<li><code>prob</code> :: <code>numeric(n)</code>
Numeric vector of <code>param$nlevels</code> probabilities, which is uniform by default.</li>
</ul>

Fields

See <a rd-options="" href="/link/Sampler1D?package=paradox&version=0.2.0" data-mini-rdoc="paradox::Sampler1D">Sampler1D</a>.

Methods

Sampling from a discrete distribution, for a <a rd-options='' href='ParamFct'>ParamFct</a> or <a rd-options='' href='ParamLgl'>ParamLgl</a>.

Sampler1DCateg Class — Sampler1DCateg

<a rd-options='R6:R6Class' href='R6::R6Class'>R6::R6Class</a> inheriting from <a rd-options='' href='Sampler1D'>Sampler1D</a>.

<pre>smpl = Sampler1DCateg$new(param, prob = NULL)
</pre>
<ul>
<li><code>param</code> :: <a rd-options='' href='Param'>Param</a>
Domain / support of the distribution we want to sample from.</li>
<li><code>prob</code> :: <code>numeric()</code>
Numeric vector of <code>param$nlevels</code> probabilities, which is uniform by default.</li>
</ul>

Sampler1DCateg: Sampler1DCateg Class

Description

Arguments

Format

Construction

Fields

Methods

See Also