Name
Abstract | ||
|---|---|---|
Lattice conditional independence (LCI) models for multivariate normal data recently have been introduced for the analysis of non‐monotone missing data patterns and of nonnested dependent linear regression models (\equiv seemingly unrelated regressions). It is shown here that the class of LCI models coincides with a subclass of the class of graphical Markov models determined by acyclic digraphs (ADGs), namely, the subclass of transitive ADG models. An explicit graph‐theoretic characterization of those ADGs that are Markov equivalent to some transitive ADG is obtained. This characterization allows one to determine whether a specific ADG D is Markov equivalent to some transitive ADG, hence to some LCI model, in polynomial time, without an exhaustive search of the (possibly superexponentially large) equivalence class [D]. These results do not require the existence or positivity of joint densities. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1023/A:1018901032102 | Ann. Math. Artif. Intell. |
Keywords | Field | DocType |
Distributive Lattice,Conditional Independence,Multivariate Normal Distribution,Chordal Graph,Undirected Edge | Discrete mathematics,Combinatorics,Conditional independence,Markov model,Markov chain,Multivariate normal distribution,Missing data,Equivalence class,Mathematics,Linear regression,Transitive relation | Journal |
Volume | Issue | ISSN |
21 | 1 | 1573-7470 |
Citations | PageRank | References |
2 | 0.47 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steen A. Andersson | 1 | 16 | 3.69 |
| David Madigan | 2 | 190 | 22.89 |
| Michael D. Perlman | 3 | 30 | 5.17 |
| Christopher M. Triggs | 4 | 3 | 1.19 |