A new directed tree structure learning framework for zero-inflated compositional nodes uses KL divergence scoring and column-stochastic transition matrices for conditional expectations, with proven consistency and finite-sample guarantees.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Develops tests for no dependence and partial effects in global Fréchet regression using random multipliers for null distributions and the Cauchy combination method, with consistency results and simulations on networks and spheres.
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Structure Learning for Directed Trees with Zero-Inflated Compositional Nodes
A new directed tree structure learning framework for zero-inflated compositional nodes uses KL divergence scoring and column-stochastic transition matrices for conditional expectations, with proven consistency and finite-sample guarantees.
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Inference for Fr\'echet Regression
Develops tests for no dependence and partial effects in global Fréchet regression using random multipliers for null distributions and the Cauchy combination method, with consistency results and simulations on networks and spheres.