Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.12692.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T22:31:24.923420Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T07:29:39.506173Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 3be2fbb9-8b35-4c6b-a5f8-746654d36b40 · inbound
Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation cites this paper.
Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T22:31:24.923420Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a597387-113c-4d05-9e05-c8a2d645c337 · inbound
Universal priors: solving empirical Bayes via Bayesian inference and pretraining cites this paper.
Universal priors: solving empirical Bayes via Bayesian inference and pretraining Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
Reference 1956
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:03:08.164630Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25beefee-e05b-4978-a0ed-b4cf6a27bbea · inbound
Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures cites this paper.
Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:31:01.160200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2b2b2ba2-ac13-433e-9bd9-c77d5d6a1fdb · inbound
Fast computation and theoretical guarantees for the NPMLE in exponential family mixtures cites this paper.
Fast computation and theoretical guarantees for the NPMLE in exponential family mixtures Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.609197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1502bcb0-8172-4407-bce7-fd0f2bee3295 · inbound
Quasi-Bayes empirical Bayes estimation of sums of random variables cites this paper.
Quasi-Bayes empirical Bayes estimation of sums of random variables Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T07:29:39.507471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.