HDIofMCMC: Compute Highest-Density Interval
In hBayesDM: Hierarchical Bayesian Modeling of Decision-Making Tasks
HDIofMCMC 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
HDIofMCMC(sampleVec, credMass = 0.95)
Arguments
sampleVec
A vector of representative values from a probability distribution (e.g., MCMC samples).
credMass
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. 23, 2022, 9:06 a.m.
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| HDIofMCMC | 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
HDIofMCMC(sampleVec, credMass = 0.95)
Arguments
sampleVec |
A vector of representative values from a probability distribution (e.g., MCMC samples). |
credMass |
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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