Name
Abstract | ||
|---|---|---|
n asymptotic theory is developed for computing volumes of regions in the parameter space of a directed Gaussian graphical model that are obtained by bounding partial correlations. We study these volumes using the method of real log canonical thresholds from algebraic geometry. Our analysis involves the computation of the singular loci of correlation hypersurfaces. Statistical applications include the strong-faithfulness assumption for the PC algorithm and the quantification of confounder bias in causal inference. A detailed analysis is presented for trees, bow ties, tripartite graphs, and complete graphs. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10208-014-9205-0 | Foundations of Computational Mathematics |
Keywords | Field | DocType |
Causal inference,Real log canonical threshold,Resolution of singularities,Gaussian graphical model,Algebraic statistics,Singular learning theory,62H05,62H20,14Q10 | Mathematical optimization,Partial correlation,Algebraic geometry,Mathematical analysis,Resolution of singularities,Gaussian,Parameter space,Graphical model,Algebraic statistics,Mathematics,Computation | Journal |
Volume | Issue | ISSN |
14 | 5 | 1615-3375 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shaowei Lin | 1 | 319 | 16.43 |
| Caroline Uhler | 2 | 129 | 16.91 |
| Bernd Sturmfels | 3 | 926 | 136.85 |
| Peter Bühlmann | 4 | 27 | 3.60 |