pcalg (version 1.0-0)

binCItest: Test for (conditional) independence for binary data

Description

This function tests for (condtitional) independence between binary random variables. The function was organized in a way, so that it can easily be used in skeleton, pc, fci.

Usage

binCItest(x, y, S, suffStat)

Arguments

x

Position of node X in adjacency matrix

y

Position of node Y in adjacency matrix

S

Position of set of nodes in adjacency matrix on which is conditioned

suffStat

A list with two elements: (1) Element "dm" containing the data matrix (columns are variables, rows are samples) and (3) element "adaptDF" as a boolean variable indicating whether to lower the degrees of freedom by one for each zero count.

Value

• The p-value of the test is returned.

Details

This function is based on gSquareBin; see its help file for details.

See Also

dsepTest, gaussCItest and disCItest for similar functions for a d-separation oracle, conditional independence test on gaussian variables and conditional independence test on discrete variables, respectively.

Examples

## Simulate data
set.seed(123)
x <- sample(1:2,100,TRUE)
y <- sample(1:2,100,TRUE)
z <- sample(1:2,100,TRUE)
dat <- cbind(x,y,z)

suffStat <- list(dm = dat, adaptDF = FALSE)
binCItest(1,3,2,suffStat)