Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2505.08288.
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 2026-08-07T13:20:17.697308Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-04T22:12:40.624315Z
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 533cfa3d-cafe-43e4-99f5-81ee3ba198df · inbound
Handling bounded response in high dimensions: a Horseshoe prior Bayesian Beta regression approach cites this paper.
Handling bounded response in high dimensions: a Horseshoe prior Bayesian Beta regression approach High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:20:17.697308Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6812aedd-0916-46b5-811d-c74c878ab322 · inbound
Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding cites this paper.
Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:35:16.321855Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fd77a38-a521-4be2-bc0c-44d87a830b82 · inbound
Bayesian Pliable Lasso with Horseshoe Prior for Interaction Effects in GLMs with Missing Responses cites this paper.
Bayesian Pliable Lasso with Horseshoe Prior for Interaction Effects in GLMs with Missing Responses High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-04T22:12:40.630348Z
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.