Description Usage Arguments Examples

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

1 | ```
impliedConditionalIndependencies(x, type = "missing.edge", max.results = Inf)
``` |

`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 |

1 2 3 4 | ```
g <- dagitty( "dag{ x -> m -> y }" )
impliedConditionalIndependencies( g ) # one
latents( g ) <- c("m")
impliedConditionalIndependencies( g ) # none
``` |

```
x _||_ y | m
```

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