Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2106.03322.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-01T01:43:03.338128Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T12:45:44.957248Z
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 cacca054-c4be-4ec4-8a63-0be1f25f77d6 · inbound
Hierarchical Clustering As a Novel Solution to the Notorious Multicollinearity Problem in Observational Causal Inference cites this paper.
Hierarchical Clustering As a Novel Solution to the Notorious Multicollinearity Problem in Observational Causal Inference Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T12:45:44.958852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.