subject: Estimate subject's full network: runs exhaustive search on...

In schw4b/multdyn: Dynamic Graphical Models

Description

Estimate subject's full network: runs exhaustive search on very node.

Usage

subject(
  X,
  id = NULL,
  nbf = 15,
  delta = seq(0.5, 1, 0.01),
  cpp = TRUE,
  priors = priors.spec(),
  path = getwd(),
  method = "exhaustive"
)

Arguments

X	array with dimensions timeseries x nodes.
id	subject ID. If set, results are saved to a txt file.
nbf	Log Predictive Likelihood will sum from (and including) this time point.
delta	a vector of potential values for the discount factor.
cpp	boolean true (default): fast C++ implementation, false: native R code.
priors	list with prior hyperparameters.
path	a path where results are written.
method	ether exhaustive, foward, backward, or both.

Value

store list with results.

Examples

data("utestdata")
# select only 3-nodes to speed-up this example
sub=subject(myts[,1:3]) 
sub=subject(myts[,1:3], method="both")

schw4b/multdyn documentation built on Dec. 14, 2021, 7:39 a.m.