hdi: Compute Highest-Density Interval
In hBayesDM: Hierarchical Bayesian Modeling of Decision-Making Tasks
hdi R Documentation
Compute Highest-Density Interval
Description
Computes the highest density interval from a sample of representative values,
estimated as shortest credible interval.
Based on John Kruschke's codes.
Usage
hdi(sample_vec, ci_prob = 0.95)
Arguments
sample_vec
A vector of representative values from a probability distribution (e.g., MCMC samples).
ci_prob
A scalar between 0 and 1, indicating the mass within the credible interval that is to be estimated.
Value
A vector containing the limits of the HDI
hBayesDM documentation built on Sept. 10, 2026, 1:12 a.m.
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| hdi | R Documentation |
Compute Highest-Density Interval
Description
Computes the highest density interval from a sample of representative values, estimated as shortest credible interval. Based on John Kruschke's codes.
Usage
hdi(sample_vec, ci_prob = 0.95)
Arguments
sample_vec |
A vector of representative values from a probability distribution (e.g., MCMC samples). |
ci_prob |
A scalar between 0 and 1, indicating the mass within the credible interval that is to be estimated. |
Value
A vector containing the limits of the HDI
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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