impliedConditionalIndependencies: List Implied Conditional Independencies

In dagitty: Graphical Analysis of Structural Causal Models

Description

Generates a list of conditional independence statements that must hold in every probability distribution compatible with the given model.

Usage

impliedConditionalIndependencies(x, type = "missing.edge", max.results = Inf)

Arguments

x	the input graph, a DAG, MAG, or PDAG.
type	can be one of "missing.edge", "basis.set", or "all.pairs". With the first, one or more minimal testable implication (with the smallest possible conditioning set) is returned per missing edge of the graph. With "basis.set", one testable implication is returned per vertex of the graph that has non-descendants other than its parents. Basis sets can be smaller, but they involve higher-dimensional independencies, whereas missing edge sets involve only independencies between two variables at a time. With "all.pairs", the function will return a list of all implied conditional independencies between two variables at a time. Beware, because this can be a very long list and it may not be feasible to compute this except for small graphs.
max.results	integer. The listing of conditional independencies is stopped once this many results have been found. Use Inf to generate them all. This applies only when type="missing.edge" or type="all".

Examples

g <- dagitty( "dag{ x -> m -> y }" )
impliedConditionalIndependencies( g ) # one
latents( g ) <- c("m")
impliedConditionalIndependencies( g ) # none

Example output

x _||_ y | m

dagitty documentation built on Jan. 21, 2021, 5:07 p.m.