generate.distribution

<a href="https://lifecycle.r-lib.org/articles/stages.html#stable"><img src="figures/lifecycle-stable.svg?package=distributional&version=0.5.0" alt="[Stable]"></a>
Generate random samples from probability distributions.

Vectorised distribution objects with tools for manipulating,
visualising, and using probability distributions. Designed to allow model
prediction outputs to return distributions rather than their parameters,
allowing users to directly interact with predictive distributions in a
data-oriented workflow. In addition to providing generic replacements for
p/d/q/r functions, other useful statistics can be computed including means,
variances, intervals, and highest density regions.

Mitchell O'Hara-Wild

distributional

Vectorised Probability Distributions

Matthew Kay

Alex Hayes

Rob Hyndman

Earo Wang

Vencislav Popov

generate.distribution function

<dl><dt>x</dt>
<dd>The distribution(s).</dd>
<dt>times</dt>
<dd>The number of samples.</dd>
<dt>...</dt>
<dd>Additional arguments used by methods.</dd></dl>

Arguments

<a href='https://lifecycle.r-lib.org/articles/stages.html#stable'><img src='figures/lifecycle-stable.svg' alt='[Stable]' /></a>
Generate random samples from probability distributions.

Randomly sample values from a distribution — generate.distribution

<dl>

<dt>x</dt>
<dd>The distribution(s).</dd>


<dt>times</dt>
<dd>The number of samples.</dd>


<dt>...</dt>
<dd>Additional arguments used by methods.</dd>

</dl>

generate.distribution: Randomly sample values from a distribution

Description

Usage

Arguments