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Estimate subject's full network: runs exhaustive search on very node.
subject( X, id = NULL, nbf = 15, delta = seq(0.5, 1, 0.01), cpp = TRUE, priors = priors.spec(), path = getwd(), method = "exhaustive" )
array with dimensions timeseries x nodes.
subject ID. If set, results are saved to a txt file.
Log Predictive Likelihood will sum from (and including) this time point.
a vector of potential values for the discount factor.
boolean true (default): fast C++ implementation, false: native R code.
list with prior hyperparameters.
a path where results are written.
ether exhaustive, foward, backward, or both.
store list with results.
# NOT RUN { data("utestdata") # select only 3-nodes to speed-up this example sub=subject(myts[,1:3]) sub=subject(myts[,1:3], method="both") # }
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