zf: Gaussian conditional independence test

Description Usage Arguments Value References Examples

Description

Gaussian conditional independence test. See the zf function in the bnlearn package for more details.

Usage

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zf(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 the 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

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

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

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