Computes the highest density interval from a sample of representative values,
estimated as shortest credible interval.
Based on John Kruschke's codes.

Fit an array of decision-making tasks with computational models in
a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of
various computational models with a single line of coding
(Ahn et al., 2017) <doi:10.1162/CPSY_a_00002>.

Woo-Young Ahn

hBayesDM

Hierarchical Bayesian Modeling of Decision-Making Tasks

Nate Haines

Lei Zhang

Jinwoo Jeong

Harhim Park

Jaeyeong Yang

Jethro Lee

hdi function

<dl><dt>sample_vec</dt>
<dd>A vector of representative values from a probability distribution (e.g., MCMC samples).</dd>
<dt>ci_prob</dt>
<dd>A scalar between 0 and 1, indicating the mass within the credible interval that is to be estimated.</dd></dl>

Arguments

Compute Highest-Density Interval — hdi

<dl>

<dt>sample_vec</dt>
<dd>A vector of representative values from a probability distribution (e.g., MCMC samples).</dd>


<dt>ci_prob</dt>
<dd>A scalar between 0 and 1, indicating the mass within the credible interval that is to be estimated.</dd>

</dl>

hdi: Compute Highest-Density Interval

Description

Usage

Value

Arguments