smcmig: The sequential Monte Carlo permutation test (smc-mi-g)

In ParallelPC: Paralellised Versions of Constraint Based Causal Discovery Algorithms

Description

The sequential Monte Carlo permutation test. See bnlearn package for more details.

Usage

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

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