dot-hdi: Compute Highest Posterior Density intervals.
In MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage
.hdi R Documentation
Compute Highest Posterior Density intervals.
Description
Compute Highest Posterior Density intervals.
Usage
.hdi(samps, prob, add_zero = FALSE)
Arguments
samps
MCMC sample matrix.
prob
Numeric in (0,1).
add_zero
Logical (Default: FALSE) - Whether to add zero to samples. Useful for unidirectional effects.
Value
Matrix of HDIs.
Author(s)
Stephen Martin
MIRES documentation built on June 8, 2025, 10:55 a.m.
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.
| .hdi | R Documentation |
Compute Highest Posterior Density intervals.
Description
Compute Highest Posterior Density intervals.
Usage
.hdi(samps, prob, add_zero = FALSE)
Arguments
samps |
MCMC sample matrix. |
prob |
Numeric in (0,1). |
add_zero |
Logical (Default: FALSE) - Whether to add zero to samples. Useful for unidirectional effects. |
Value
Matrix of HDIs.
Author(s)
Stephen Martin
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.