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Paper Citation Record · LEDGER

Theory and Algorithms for Forecasting Time Series

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1803.05814.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1803.05814 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:23:47.893318Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-12T17:23:47.992120Z

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 fb0b4084-fe3b-4483-9e27-b8dc94399df0 · inbound

Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression cites this paper.

Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression Theory and Algorithms for Forecasting Time Series

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-12T17:23:47.995371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T17:23:47.893318Z digest=sha256:effccebd9d286fd1fb186f51f39957f1e4cd53831ae8879a86e49a2db61d0150

Observation b5f3dd56-c483-47db-a6a9-5c105799b79f · inbound

Learning Ergodic Dynamical Systems from a Finite Trajectory cites this paper.

Learning Ergodic Dynamical Systems from a Finite Trajectory Theory and Algorithms for Forecasting Time Series

Reference 156

Resolution
unresolved
no resolver link, observed 2026-08-01T04:58:39.989678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:58:39.989678Z digest=sha256:07ea554c0d924ee32db04716696b960a668454d9f3bae93ca0b15a45fd27a3ce