bounder_range

Estimate the bounds of the distribution a sample came from using the range of the sample.
Use with the <code>bounder</code> argument to <code>density_bounded()</code>.
Supports automatic partial function application.

Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for
visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as
frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as
bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include
but are not limited to: points with multiple uncertainty intervals,
eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>,
density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>,
quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>,
complementary cumulative distribution function
barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>,
and fit curves with multiple uncertainty ribbons.

Matthew Kay

ggdist

Visualizations of Distributions and Uncertainty

Brenton M. Wiernik

bounder_range function

<dl><dt>x</dt>
<dd>numeric vector containing a sample to estimate the bounds of.</dd></dl>

Arguments

Estimate bounds of a distribution using the range of the sample — bounder_range

<dl>

<dt>x</dt>
<dd>numeric vector containing a sample to estimate the bounds of.</dd>

</dl>

bounder_range: Estimate bounds of a distribution using the range of the sample

Description

Usage

Value

Arguments

Details

See Also