computeScoreMat: auxiliary file for CAM: Computes the initial score matrix.

In CAM: Causal Additive Model (CAM)

Description

auxiliary file to CAM. Computes the initial score matrix.

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.

Value

A list with elements

scoreMat	The score matrix. scoreMat[i,j] contains the gain in score if we consider i being a parent of j
rowParents	Contains the row names of the score matrix. Only relevant if numParents > 1.
scoreEmtpyNodes	Vector containing the scores of each node in the empty graph without any edges.

Note

This is an auxiliary file for CAM.

Author(s)

J. Peters ([e-mail]) and J. Ernest ([e-mail])

References

P. B\"uhlmann, J. Peters, J. Ernest: CAM: Causal Additive Models, high-dimensional Order Search and Penalized Regression Annals of Statistics 42:2526-2556, 2014.

See Also

CAM

CAM documentation built on May 2, 2019, 8:24 a.m.