Sampler1DUnif

Uniform random sampler for arbitrary (bounded) parameters.

datasets

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

Sampler1DUnif function

<a rd-options="R6:R6Class" href="/link/R6%3A%3AR6Class?package=paradox&version=0.1.0&to=R6%3AR6Class" data-mini-rdoc="R6:R6Class::R6::R6Class">R6::R6Class</a> inheriting from <a rd-options="" href="/link/Sampler1D?package=paradox&version=0.1.0" data-mini-rdoc="paradox::Sampler1D">Sampler1D</a>.

Format

<pre>smpl = Sampler1DUnif$new(param)
</pre>
<ul>
<li><code>param</code> :: <a rd-options="" href="/link/Param?package=paradox&version=0.1.0" data-mini-rdoc="paradox::Param">Param</a>
Domain / support of the distribution we want to sample from.</li>
</ul>

Construction

See <a rd-options="" href="/link/Sampler1D?package=paradox&version=0.1.0" data-mini-rdoc="paradox::Sampler1D">Sampler1D</a>.

Fields

Methods

Sampler1DUnif Class — Sampler1DUnif

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

<pre>smpl = Sampler1DUnif$new(param)
</pre>
<ul>
<li><code>param</code> :: <a rd-options='' href='Param'>Param</a>
Domain / support of the distribution we want to sample from.</li>
</ul>

Sampler1DUnif: Sampler1DUnif Class

Description

Arguments

Format

Construction

Fields

Methods

See Also