posterior_density_funs_sigmas: Create marginal posterior density function approximations for...
In MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage
Description
Usage
Arguments
Details
Value
Author(s)
Description
For each RE-SD, approximates the marginal posterior density from MCMC samples for use in BF calculations.
Usage
1
posterior_density_funs_sigmas(mires, add_zero = TRUE, ...)
Arguments
mires
mires object.
add_zero
Logical (Default: TRUE). Whether to add a zero to samples.
...
Args passed onto .density.stan.
Details
Starts by computing (lower-bounded) logspline approximations.
If these fail, it uses the Dirichlet process with positive-normal kernels as an approximation.
Value
List of approximate density functions.
Author(s)
Stephen Martin
MIRES documentation built on Feb. 22, 2021, 5:10 p.m.
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Description Usage Arguments Details Value Author(s)
Description
For each RE-SD, approximates the marginal posterior density from MCMC samples for use in BF calculations.
Usage
1 | posterior_density_funs_sigmas(mires, add_zero = TRUE, ...)
|
Arguments
mires |
mires object. |
add_zero |
Logical (Default: TRUE). Whether to add a zero to samples. |
... |
Args passed onto .density.stan. |
Details
Starts by computing (lower-bounded) logspline approximations. If these fail, it uses the Dirichlet process with positive-normal kernels as an approximation.
Value
List of approximate density functions.
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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