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" or "basis.set". With the former, one testable implication is returned per missing edge of the graph. With the latter, 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 bivariate independencies.
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".

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 May 2, 2019, 5:53 p.m.