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growcurves (version 0.2.4.1)

mmCplusDpPost: Bayesian mixed effects model with a DP prior on by-subject effects and CAR prior on a set of multiple membership effects

Description

An internal function to dpgrowmm

Usage

mmCplusDpPost(y, X, Z, Wcase, Wsubject, Omega, omegaplus, groups, subjects, niter, nburn, nthin, strength.mm, shapealph, ratebeta)

Arguments

y
An N x 1 response (of subject-measure cases)
X
Fixed effects design matrix
Z
Random effects design matrix. Assumed grouped by subjects
Wcase
An N x 1 multiple membership weight matrix to map supplemental random effects
Wsubject
An P.aff x S multiple membership weight matrix with rows equal to number of unique affected subjects
Omega
An S x S unnormalized adjacency matrix with entries equal to 1 where two effects communicate and 0, otherwise. Diagonal elements are zero
omegaplus
S x 1 vector of row sums of Omega
groups
S x 1 vector of group identifiers for each effect. Effects within each group communicate. Effects don't communicate across groups.
subjects
An N x 1 set of subject identifiers
niter
The number of MCMC iterations
nburn
The number of MCMC burn-in iterations to discard
nthin
The step increment of MCMC samples to return
strength.mm
The shape and rate parameters for the $\Gamma$ prior on the CAR precision parameter, $\tau_{\gamma}$
shapealph
The shape parameter for the $\Gamma$ prior on the DP concentration parameter. The rate parameter is set of 1.
ratebeta
The rate parameter for the $\Gamma$ prior on the DP concentration parameter. Default value is 1.

Value

res A list object containing MCMC runs for all model parameters.

See Also

dpgrow