Partial correlation hypersurfaces in Gaussian graphical models

Jan Draisma (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review


We derive a combinatorial sufficient condition for a partial correlation hypersurface in the parameter space of a directed Gaussian graphical model to be nonsingular, and speculate on whether this condition can be used in algorithms for learning the graph. Since the condition is fulfilled in the case of a complete DAG on any number of vertices, the result implies an affirmative answer to a question raised by Lin–Uhler–Sturmfels–Bühlmann.
Original languageEnglish
Pages (from-to)439-446
Number of pages8
JournalAlgebraic Combinatorics
Issue number3
Publication statusPublished - 6 Jun 2019


  • Gaussian graphical models
  • Partial correlation
  • Trek separation


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