pValueAfterMultipleTesting

the conditional independence test result (of type <code>CITestResult</code>)

dsep

the p values associated with the variables at size n of conditioning set (list [[n]] -> [pvals])

adjC.pvals.at.n

the p value adjustment method (same as in p.adjust())

p.value.adjust.method

This function is only for DDGraph with multiple testing correction enabled. The overall procedure is similar to
that described in (Li&Wang 2009). This is a helper function for <code>DDDataSet:ncpc()</code>. The single P-value
of D-separation is substituted in the list of P-values, P-values adjusted and the resulting P-value after correction
in the context of other P-values reported.

Distinguish direct from indirect interactions in gene
regulation and infer combinatorial code from highly correlated
variables such as transcription factor binding profiles. The
package implements the Neighbourhood Consistent PC algorithm
(NCPC) and draws Direct Dependence Graphs to represent
dependence structure around a target variable. The package also
provides a unified interface to other Graphical Modelling
(Bayesian Network) packages for distinguishing direct and
indirect interactions.

pValueAfterMultipleTesting: Multiple testing correction procedure for ncpc()

Description

Usage

Arguments

Value

References