mccor: The Monte Carlo permutation test (mc-cor)

In ParallelPC: Paralellised Versions of Constraint Based Causal Discovery Algorithms

Description

The Monte Carlo permutation test for Pearson's chi-square. See bnlearn package for details.

Usage

mccor(x, y, S, suffStat)

Arguments

x,y,S	It is tested, whether x and y are conditionally independent given the subset S of the remaining nodes. x, y, S all are integers, corresponding to variable or node numbers.
suffStat	The dataset in matrix format with rows are samples and columns are variables.

Value

The p-value of the test.

References

Marco Scutari (2010). Learning Bayesian Networks with the bnlearn R Package. Journal of Statistical Software, 35(3), 1-22.

Examples

##########################################
## Using mccor
##########################################
library(bnlearn)
library(pcalg)
data("gmG")
suffStat<-gmG$x
mccor(1,2,3,suffStat)

ParallelPC documentation built on May 2, 2019, 9:14 a.m.