hpd: Empirical Highest Posterior Density Interval
In robustBLME: Robust Bayesian Linear Mixed-Effects Models using ABC
Description
Usage
Arguments
Value
Description
Computes the Highest Posterior Density (HPD) interval from a posterior sample. Works only for scalar marginal posteriors.
Usage
1
hpd(x, prob = 0.95)
Arguments
x
a univariate or a posterior sample for a scalar parameter.
prob
posterior probability content.
Value
vector of two doubles.
robustBLME documentation built on May 1, 2019, 6:34 p.m.
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Description Usage Arguments Value
Description
Computes the Highest Posterior Density (HPD) interval from a posterior sample. Works only for scalar marginal posteriors.
Usage
1 | hpd(x, prob = 0.95)
|
Arguments
x |
a univariate or a posterior sample for a scalar parameter. |
prob |
posterior probability content. |
Value
vector of two doubles.
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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