bSCMdeConfoundingGraphFunc: bSCMdeConfoundingGraphFunc function
In BiCausality: Binary Causality Inference Framework

bSCMdeConfoundingGraphFunc

R Documentation

bSCMdeConfoundingGraphFunc function

This function removes any association/dependency of variables i,j that have any confounding factor k s.t. given k, i and j are independent.

bSCMdeConfoundingGraphFunc(dat, IndpThs = 0.05, alpha = 0.05)

`dat`	is the result of inferring dependencies between all pairs of variables from `bSCMDepndentGraphFunc()`.
`IndpThs`	is a threshold for the degree of dependency. In the independence test, to claim that any variables are dependent, the dependency degree must greater than this value significantly. The default is 0.05.
`alpha`	is a significance threshold for hypothesis tests (Mann Whitney) that deploys for testing degrees of dependency, association direction, and causal direction. The default is 0.5.

This function returns an adjacency matrix of dependencies that have no confounding factors.

`E1`	An adjacency matrix of undirected graph after filtering associations without true causal directions from any confounding factor.
`E2`	A matrix of associations that have confounding factors where `E2[i,j]=0` if no confounding factor and `E2[i,j]=k` if k is a confounding factor of i and j.