dot-hdi: Compute Highest Posterior Density intervals.
In MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage
Description
Usage
Arguments
Value
Author(s)
Description
Compute Highest Posterior Density intervals.
Usage
1
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 Feb. 22, 2021, 5:10 p.m.
R Package Documentation
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Description Usage Arguments Value Author(s)
Description
Compute Highest Posterior Density intervals.
Usage
1 |
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.
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