prior_sampling {graphicalEvidence} | R Documentation |
Sample The Precision Matrix
Description
Takes specified prior_name and relevant parameters to sample the precision matrix nmc times after discarding the first number of runs specified by burnin.
Usage
prior_sampling(
p,
burnin,
nmc,
prior_name = c("BGL", "GHS", "G_Wishart"),
G = NULL,
V = NULL,
alpha = NULL,
lambda = NULL
)
Arguments
p |
The dimension of the precision matrix that will be sampled |
burnin |
The number of iterations the MCMC sampler should iterate through and discard before beginning to save results |
nmc |
The number of samples that will be drawn |
prior_name |
The name of the prior for which the marginal should be calculated, this is one of 'Wishart', 'BGL', 'GHS', 'G_Wishart' |
G |
The adjacency matrix when specifying 'G_Wishart' prior |
V |
The scale matrix when specifying 'Wishart' or 'G_Wishart' prior |
alpha |
A number specifying alpha for the priors of 'Wishart' and 'G_Wishart' |
lambda |
A number specifying lambda for the priors of 'BGL' and 'GHS' prior |
Value
An array of dim nmc x p x p where each p x p slice is one sample of the precision matrix
Examples
# Draw 5000 samples of the precision matrix for GHS prior distribution with
# parameter lambda set to 1
prior_sampling(5, 1e3, 5e3, 'GHS', lambda=1)