How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
DAG Markov equivalence, patterns, and CPDAGs
Definition
Fix a finite vertex set . For a DAG on , its skeleton is the undirected graph with edge exactly when contains or . An unshielded triple is a triple of distinct vertices with edges and in the skeleton and no edge between and . It is an unshielded collider (also called a v-structure) when its arrows are . Two DAGs on are Markov equivalent when they induce the same d-separation relations: for every pairwise disjoint , and are d-separated by in one DAG exactly when they are d-separated by in the other. The equivalence class of is denoted .
A partially directed acyclic graph (PDAG) on is a simple mixed graph whose directed edges contain no directed cycle. A consistent DAG extension of a PDAG preserves every directed edge, orients every undirected edge, is acyclic, and creates no unshielded collider absent from the PDAG. For an equivalence class with a common skeleton, its completed pattern directs an edge exactly when that orientation occurs in every DAG of the class and leaves the edge undirected when both orientations occur. A completed partially directed acyclic graph (CPDAG) for is this unique completed pattern when its consistent DAG extensions are exactly . Thus its directed edges are compelled, while each undirected edge occurs in both directions among its consistent extensions.
Definition references
Depends on
Used by
- Population PC causal-discovery algorithm Algorithm
- A complete three-vertex skeleton has several equivalent DAGs Example
- A hidden common cause is observationally indistinguishable from an edge Example
- PC distinguishes a chain from an unshielded collider Example
- A separating set identifies an unshielded collider Lemma
- The background-free Meek rules complete a CPDAG Lemma
- DAG Markov equivalence is determined by skeletons and unshielded colliders Theorem
- High-dimensional consistency of Gaussian PC structure learning Theorem
- The PC algorithm recovers the oracle CPDAG Theorem
Dependency tree · one level
1 result within one dependency step of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Meek, Causal Inference and Causal Explanation with Background Knowledge, §1.1 (standard reference, not scraped)
- Lauritzen, Graphical Models lecture notes, §2.6 (standard reference, not scraped)