Bayesian tools

HPDregions(data::AbstractArray, coverage)

Compute the highest posterior density (HPD) regions based on a kernel density estimate of the data.

coverage ∈ (0,1) is the probability mass to be included in the HPD region.

Examples

julia> hpdregion, actualCoverage = HPDregions(randn(100), 0.95)

HPDregions(d::UnivariateDistribution, coverage)

Compute the highest posterior density (HPD) regions for the distribution d.

coverage ∈ (0,1) is the probability mass to be included in the HPD region.

Examples

julia> hpdregion, actualCoverage = HPDregions(Normal(0,1), 0.95)