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Paper Citation Record · LEDGER

Change Point Detection in the Mean of High-Dimensional Time Series Data under Dependence

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1903.07006.

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

pith.paper-citation-record.v1
1903.07006 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T09:25:37.723235Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T20:17:21.579403Z

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 7244a772-89c7-4845-80c4-81fe12fea7cc · inbound

High Dimensional Change Point Models for Two-Directional Data cites this paper.

High Dimensional Change Point Models for Two-Directional Data Change Point Detection in the Mean of High-Dimensional Time Series Data under Dependence

Reference 89

Resolution
metadata mismatch
local_arxiv, observed 2026-07-02T20:17:21.580650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-27T20:46:26.231549Z digest=sha256:a02c5c2a62924caa814e44cc429e193afb7f773dca9bd5c1a800d4bdab9853f4

Observation e04a983a-7687-4756-a065-eb32eb485348 · inbound

High-Dimensional Change Point Analysis for Temporally Dependent Data cites this paper.

High-Dimensional Change Point Analysis for Temporally Dependent Data Change Point Detection in the Mean of High-Dimensional Time Series Data under Dependence

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T09:25:37.723235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T09:25:37.723235Z digest=sha256:95ad5747334948e84f1613aea83ee9b0928152a51f06090a4602d2f0620da1bc