msfit_ggm-class {mombf}

Class "msfit_ggm"

Description

Stores the output of Bayesian Gaussian graphical model selection and averaging, as produced by function modelSelectionGGM. The class extends a list, so all usual methods for lists also work for msfit_ggm objects, e.g. accessing elements, retrieving names etc.

Methods are provided to obtain parameter estimates, posterior intervals (Bayesian model averaging), and posterior probabilities of parameters being non-zero

Objects from the Class

Objects are created by a call to modelSelectionGGM.

Slots

The class extends a list with elements:

postSample

Sparse matrix (dgCMatrix) with posterior samples for the Gaussian precision (inverse covariance) parameters. Each row is a posterior sample. Within each row, only the upper-diagonal of the precision matrix is stored in a flat manner. The row and column indexes are stored in indexes

indexes

For each column in postSample, it indicates the row and column of the precision matrix

p

Number of variables

priors

Priors specified when calling modelSelection

Methods

coef

Obtain BMA posterior means, intervals and posterior probability of non-zeroes

plot

Shows estimated posterior inclusion probability for each parameter vs. number of MCMC iterations. Only up to the first 5000 parameters are shown

show

signature(object = "msfit_ggm"): Displays general information about the object.

Author(s)

David Rossell

See Also

modelSelectionGGM

Examples

showClass("msfit_ggm")