Usage
computeScoreMat(X, scoreName, numParents, output, numCores, selMat, parsScore, intervMat, intervData)
Arguments
X
nxp matrix of training inputs (n data points, p dimensions)
scoreName
specifies the model type which is used to compute the score. Default is "SEMGAM" which assumes a generalized additive model class. Other options include "SEMLIN" which fits a linear model.
numParents
indicates how many parents we consider. If numParents = 1 (default), then the score matrix is of dimension (p-1) x p. If numParents = 2, then the score matrix is of dimension (p-1)(p-2) x p and so on
output
boolean indicating whether information about the progress is written to the console.
numCores
specifies the number of cores that can be used for computation.
selMat
indicating the possible parent relationships.
parsScore
additional parameters can be supported to the score function.
intervMat
the matrix intervMat has the same dimension as X. entry (i,j) == TRUE indicates that in experiment i, variable j has been intervened on.
intervData
boolean that indicates whether we use interventional data.