REVIEW 2 cited by
Estimating the history of a random recursive tree
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
This paper studies the problem of estimating the order of arrival of the vertices in a random recursive tree. Specifically, we study two fundamental models: the uniform attachment model and the linear preferential attachment model. We propose an order estimator based on the Jordan centrality measure and define a family of risk measures to quantify the quality of the ordering procedure. Moreover, we establish a minimax lower bound for this problem, and prove that the proposed estimator is nearly optimal. Finally, we numerically demonstrate that the proposed estimator outperforms degree-based and spectral ordering procedures.
Forward citations
Cited by 2 Pith papers
-
A Proof of The Changepoint Detection Threshold Conjecture in Preferential Attachment Models
Changepoint detection in preferential attachment networks is impossible when the change occurs in the last o(√n) steps, resolving the Bet-Castro-van der Hofstad conjecture.
-
Subcritical percolation and network archaeology on random recursive tree substrate networks
For random recursive trees with independent Erdős–Rényi shortcut edges, subcritical bond percolation exposes a decorated tree structure on which Jordan centrality recovers the root within a deterministic-size confidence set.
Discussion (0). Continue with ORCID to comment.