English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The Trek Separation Theorem (Sullivant et al. 2010) states necessary andsufficient conditions for a linear directed acyclic graphical model to entailfor all possible values of its linear coefficients that the rank of varioussub-matrices of the covariance matrix is less than or equal to n, for any givenn. In this paper, I extend the Trek Separation Theorem in two ways: I provethat the same necessary and sufficient conditions apply even when thegenerating model is partially non-linear and contains some cycles. Thisjustifies application of constraint-based causal search algorithms such as theBuildPureClusters algorithm (Silva et al. 2006) for discovering the causalstructure of latent variable models to data generated by a wider class ofcausal models that may contain non-linear and cyclic relations among the latentvariables.

Calculation of Entailed Rank Constraints in Partially Non-Linear and Cyclic Models