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Paper Citation Record · LEDGER

focus and focus-cpt: Fast Online Changepoint Detection in R and Python

As of 10 August 2026, this Paper Citation Record lists 100 of 234 outbound references and 0 inbound Pith citation observations for arXiv:2607.19961.

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

pith.paper-citation-record.v1
2607.19961 v1

Coverage vector

measured 100 of 234 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:14:34.600241Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 234 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved95
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7ac90ce-c5a2-41b3-9a73-603edbbf6758 · outbound

This paper cites and Killick, Rebecca , year =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Killick, Rebecca , year =

Reference 1

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source=arxiv_source observed=2026-08-01T11:14:25.415137Z digest=sha256:de8b0a1f68f56ccb202e384d4be477178ab0b34c723a383ebd5138d91563f096

Observation 6f3d42f9-5852-43da-b3e2-789950cba09a · outbound

This paper cites 2026 , eprint=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2026 , eprint=

Reference 2

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source=arxiv_source observed=2026-08-01T11:14:25.472916Z digest=sha256:345f2c11487791239bd31026cb491d24904d088e90b3b2ea93d40f8c0a76fd52

Observation 6e221071-d6c7-4801-bbad-914692df7f8a · outbound

This paper cites Journal of Statistical Software , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Software , volume=

Reference 3

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source=arxiv_source observed=2026-08-01T11:14:25.587353Z digest=sha256:4b5224ef521489a705e3ae02417ee8340471d1594c2204ff8ba3b2272dc8e7d6

Observation b5282713-cde0-4f2e-a86d-25872645fe73 · outbound

This paper cites Journal of Computational and Graphical Statistics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Computational and Graphical Statistics , volume=

Reference 4

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Observation 2e539011-f099-4d6f-84fc-0ebe35bbae10 · outbound

This paper cites SIAM review , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python SIAM review , volume=

Reference 5

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Observation e1248654-ab75-491f-bd54-227b564c1fc0 · outbound

This paper cites and Romano, Gaetano , year =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Romano, Gaetano , year =

Reference 6

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Observation 2fef6340-ba16-4343-b660-60b2ca1751ee · outbound

This paper cites 2024 , note =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2024 , note =

Reference 7

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Observation 2afd22a3-40f5-4fd9-8c05-c2ea2c1031cb · outbound

This paper cites Journal of statistical Software , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of statistical Software , volume=

Reference 8

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Observation ea7a2595-d06d-4513-bdc6-6f1342f30e11 · outbound

This paper cites IEEE transactions on biomedical circuits and systems , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE transactions on biomedical circuits and systems , volume=

Reference 9

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Observation e4e2a93a-cc60-40cb-a2a0-b6147239e16d · outbound

This paper cites Bayesian Online Changepoint Detection.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Bayesian Online Changepoint Detection

Reference 10

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source=arxiv_source observed=2026-08-01T11:14:26.406766Z digest=sha256:afbd394f584a739c90874cb6e4fb88409416ef01edf0a3cb42114e5e78d62a88

Observation 0d58335f-118a-429c-ab41-2ede9eb1d4a1 · outbound

This paper cites Neurophotonics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Neurophotonics , volume=

Reference 11

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Observation 31527093-8af5-4825-b0ae-6bfeffb8696f · outbound

This paper cites 2019 , note =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2019 , note =

Reference 12

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Observation d4456dde-7301-41de-8fdb-746586f66549 · outbound

This paper cites Cell Reports Methods , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Cell Reports Methods , volume=

Reference 13

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Observation 5799d0a1-6eea-4c9d-9ff9-0f086d1e3487 · outbound

This paper cites Mathematica Scandinavica , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematica Scandinavica , pages=

Reference 14

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Observation 380e3e19-d0d1-49c1-b264-130708e12465 · outbound

This paper cites Some minorants and majorants of random walks and L.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Some minorants and majorants of random walks and L

Reference 15

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Observation 089be98f-cca4-4dd8-a5c7-3b7cac9e53b5 · outbound

This paper cites Procedures for Reacting to a Change in Distribution.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Procedures for Reacting to a Change in Distribution

Reference 16

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Observation ecabb8fc-8f6c-4b50-93f3-834092e06ee7 · outbound

This paper cites Ross and Niall M.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Ross and Niall M

Reference 17

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Observation 5031e815-c7c3-4f6a-8e26-63854215bb96 · outbound

This paper cites Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 2 , pages =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 2 , pages =

Reference 18

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Observation 37024815-8be3-4695-b70c-df85af1c0d08 · outbound

This paper cites Scott , title =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Scott , title =

Reference 19

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Observation cf029d1b-ea0c-4661-96ef-4231add2384c · outbound

This paper cites Hawkins and Qiqi Deng , title =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Hawkins and Qiqi Deng , title =

Reference 20

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Observation 75ce09cd-3dbc-40a2-887b-0355b26a5bd1 · outbound

This paper cites Ross and Dimitris K.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Ross and Dimitris K

Reference 21

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Observation 2c209627-d880-415e-96ef-8591fc51f6a8 · outbound

This paper cites and Tartakovsky, Alexander G.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Tartakovsky, Alexander G

Reference 22

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Observation 0b20e71c-34a3-4bde-bc80-e931d4a33626 · outbound

This paper cites 1961 , journal=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 1961 , journal=

Reference 23

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Observation c7641c8a-77ba-481a-b8e0-e5021bf1b307 · outbound

This paper cites Communications in Statistics - Theory and Methods , volume =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Communications in Statistics - Theory and Methods , volume =

Reference 24

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Observation 485807ab-7872-4c8e-9384-7a1d1421a4a9 · outbound

This paper cites Sequential Analysis: Hypothesis Testing and Changepoint Detection , isbn =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential Analysis: Hypothesis Testing and Changepoint Detection , isbn =

Reference 25

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Observation 0993fdfa-439f-465f-a5fe-9ef908697d30 · outbound

This paper cites Biometrika , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=

Reference 26

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Observation 4f2590d9-cbeb-4ecb-b414-a05041ad340c · outbound

This paper cites Knowledge and Information Systems , year=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Knowledge and Information Systems , year=

Reference 27

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Observation b4d9f780-5503-45de-8f95-2d3f19e59877 · outbound

This paper cites Signal Process.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Signal Process

Reference 28

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Observation 70dad09c-3105-4fe6-b8bf-a856f284d99a · outbound

This paper cites Signal processing , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Signal processing , volume=

Reference 29

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Observation 19d2c06c-b962-40b0-8e0f-aeb4f26fa74c · outbound

This paper cites Real-time financial surveillance via quickest change-point detection methods , volume =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Real-time financial surveillance via quickest change-point detection methods , volume =

Reference 30

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Observation 9f9a3a69-346a-44b1-9fca-364fe47bc357 · outbound

This paper cites Data Science , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Data Science , volume=

Reference 31

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Observation 4d8de00a-83fa-4bd0-979f-42fc86423a46 · outbound

This paper cites Sequential change-point detection based on nearest neighbors.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential change-point detection based on nearest neighbors

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 12439745-3b74-4c27-a7d2-d319ed7c5c35 · outbound

This paper cites Change-Points: From Sequential Detection to Biology and Back , year =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Change-Points: From Sequential Detection to Biology and Back , year =

Reference 33

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Observation 7fbe6974-1e59-4a9c-8c6e-6539c577520e · outbound

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focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Arabhi, S

Reference 34

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Observation 9b9505d9-927c-4ca1-ac1e-ae98f5257f35 · outbound

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focus and focus-cpt: Fast Online Changepoint Detection in R and Python ACM Transactions on Mathematical Software (TOMS) , volume=

Reference 35

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Observation 9be122bd-ac16-490b-b864-27b57adb9a24 · outbound

This paper cites The Annals of Statistics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python The Annals of Statistics , volume=

Reference 36

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Observation 424c6a84-08bd-47a5-8000-4c3cb9718874 · outbound

This paper cites A Note on Bernoulli Trials with Dependence , volume =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python A Note on Bernoulli Trials with Dependence , volume =

Reference 37

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Observation d282856b-73e1-48b8-ac40-00b86f349bd1 · outbound

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focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2014 , publisher=

Reference 38

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Observation d3367434-e87f-494a-b2b6-0e52d4af0708 · outbound

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focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , publisher=

Reference 39

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Observation 219eef5d-581c-4764-acfc-004572fb452e · outbound

This paper cites Extreme value theory in mixture distributions and a statistical method to control the possible bias.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Extreme value theory in mixture distributions and a statistical method to control the possible bias

Reference 40

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Observation 5aa05d14-4e28-4dfb-b5c7-9ca733c3beb1 · outbound

This paper cites Approximated distributions of the weighted sum of correlated chi-squared random variables.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Approximated distributions of the weighted sum of correlated chi-squared random variables

Reference 41

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Observation 122398b1-9610-4eaa-bfb8-484edd45d489 · outbound

This paper cites A pruned dynamic programming algorithm to recover the best segmentations with 1 to Kmax change-points , year=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python A pruned dynamic programming algorithm to recover the best segmentations with 1 to Kmax change-points , year=

Reference 42

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source=arxiv_source observed=2026-08-01T11:14:29.011804Z digest=sha256:4ddfedbbbf9b47b1d9703eeb4ccd0bb8eab3532f9df95f13494d88e269561664

Observation 3a3a0606-d2b5-4e6f-a4d8-877488ffa3c6 · outbound

This paper cites Changepoint Detection in the Presence of Outliers.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Changepoint Detection in the Presence of Outliers

Reference 43

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Observation 21dd22d0-60e3-4b18-a167-17813a3e6b9f · outbound

This paper cites On optimal multiple changepoint algorithms for large data.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python On optimal multiple changepoint algorithms for large data

Reference 44

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source=arxiv_source observed=2026-08-01T11:14:29.177340Z digest=sha256:396579be5cbd81eeccae24ecb4ac145a5c43d2f7126b402c8a9dec72e5c733d5

Observation 7282fc11-93a0-4f9b-98f3-d649676bba82 · outbound

This paper cites A log-linear time algorithm for constrained changepoint detection.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python A log-linear time algorithm for constrained changepoint detection

Reference 45

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Observation 2172f0d1-1a19-414b-9286-80a85bced3be · outbound

This paper cites Journal of Statistical Software , author=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Software , author=

Reference 46

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7fec4e0b-893f-4e35-b60e-e40c9bc82d0b · outbound

This paper cites Journal of the American Statistical Association , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of the American Statistical Association , pages=

Reference 47

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source=arxiv_source observed=2026-08-01T11:14:29.403594Z digest=sha256:c9fe0f980c05f044a8acd79841636c7f352302d74fc1743dde33815dc19e55e0

Observation bb8d7afa-8099-4494-a27a-1bc1e6c050c1 · outbound

This paper cites ruptures: change point detection in Python.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python ruptures: change point detection in Python

Reference 48

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source=arxiv_source observed=2026-08-01T11:14:29.480397Z digest=sha256:7c2445ac176b9b07d12fb1c35e08cecccf618d6fdb196b759eb3a404ba9bebf0

Observation 2f13b049-aab1-4d10-bf71-264670b084d9 · outbound

This paper cites 2020 , note =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2020 , note =

Reference 49

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source=arxiv_source observed=2026-08-01T11:14:29.571000Z digest=sha256:00386e39ae796a59fb827785f0946c41f546be65767e527e61b3f30d1b353e78

Observation 4abbd942-61d9-4705-bab3-1ed86601ff3b · outbound

This paper cites Information Processing Letters , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Information Processing Letters , volume=

Reference 50

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source=arxiv_source observed=2026-08-01T11:14:29.638616Z digest=sha256:8f879daed6b3a87bdd3fe24ca43e6e769c8f644c1effc90353f845eda1af224e

Observation 9753fbe6-bf15-4457-bab8-086d9929d1b3 · outbound

This paper cites Electronic Journal of Statistics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Electronic Journal of Statistics , volume=

Reference 51

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source=arxiv_source observed=2026-08-01T11:14:29.721646Z digest=sha256:e13ee66b570ab9cb7d1c763b21acba26410867524a593b8937d1d82a4ee2fec0

Observation 8db7e468-6566-488f-9f32-521f5f847030 · outbound

This paper cites Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data

Reference 52

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source=arxiv_source observed=2026-08-01T11:14:29.805177Z digest=sha256:f06780eff51641930df16ec1f9cf11a5c933a53a98a4083bfcc77ecb9e6c84cb

Observation 7e49a87a-d4e7-40d8-9613-1e8c669ad15f · outbound

This paper cites 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) , pages=

Reference 53

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source=arxiv_source observed=2026-08-01T11:14:29.872540Z digest=sha256:6517aaf3fae219d3ee402eb65e87c8858ad3bd3971ba30bc8b7873d85e3944f6

Observation a146e28b-c78b-4572-81e6-eef486c096ed · outbound

This paper cites Neurocomputing , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Neurocomputing , volume=

Reference 54

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source=arxiv_source observed=2026-08-01T11:14:29.947094Z digest=sha256:077312a0bef2829a87e04d2542a392a1f737bd8de21cb12f55d526fd04a7e2c9

Observation 53bf3af8-725c-489d-9c8a-6a7fc158e50f · outbound

This paper cites Neural computation , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Neural computation , volume=

Reference 55

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source=arxiv_source observed=2026-08-01T11:14:30.057116Z digest=sha256:3c60298d9e6f8bfa9ac513f2a8b1a2c364008b4cbe6737678f67ccaed4cfa429

Observation 69098b68-f717-49a4-b0ac-5ce517009833 · outbound

This paper cites 2004 , publisher=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2004 , publisher=

Reference 56

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source=arxiv_source observed=2026-08-01T11:14:30.141954Z digest=sha256:eb5f04f98a9539cf3f24d0033221d5975c1357e4c828686cb551e4f8c041c1a7

Observation c1fd1da9-2ddf-4ffc-988a-159c9663bf2c · outbound

This paper cites Journal of the American Statistical Association , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of the American Statistical Association , volume=

Reference 57

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source=arxiv_source observed=2026-08-01T11:14:30.230198Z digest=sha256:f0c5651745d93313051f297d306e8da55ea5aa9106de6a029e7a77c5ca8eeb83

Observation 98d15cd0-220c-4afb-bcdd-57c65bbde72d · outbound

This paper cites Sequential Analysis , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential Analysis , volume=

Reference 58

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source=arxiv_source observed=2026-08-01T11:14:30.312242Z digest=sha256:69eff713da65b248c77f99f78e2ac5b584f5729d2a929a8bbe9006d695ea1242

Observation 4177de05-fb11-45c2-b49f-1996eea1b684 · outbound

This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=

Reference 59

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no resolver link, observed 2026-08-01T11:14:30.400117Z

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source=arxiv_source observed=2026-08-01T11:14:30.400117Z digest=sha256:5e2f659d23ad20aeec66af5e052367bbd9a662c8a8ac8a3bd273a87c686ee310

Observation 1225243c-40a5-4e5c-961b-3f2d748993da · outbound

This paper cites Biometrika , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=

Reference 60

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source=arxiv_source observed=2026-08-01T11:14:30.442474Z digest=sha256:4a1a628da775c5aca24f7103fa36372516d8cbabf7c96985bb899ca3c308d50a

Observation 1783637e-b9ab-491d-add2-9c533ad23bbb · outbound

This paper cites IEEE Transactions on Information Theory , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Transactions on Information Theory , volume=

Reference 61

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source=arxiv_source observed=2026-08-01T11:14:30.521787Z digest=sha256:906adeae091158c6101d73b86f94114442f6fa7f0d8555187f7b4d26235df631

Observation e52a256f-a05b-4bcb-8690-718ee5818db2 · outbound

This paper cites Biometrika , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=

Reference 62

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source=arxiv_source observed=2026-08-01T11:14:30.599023Z digest=sha256:96e13dbb4866f7949d3981649c6c03f4ef1e86e398e45e1c77cb3980bcf865c1

Observation 8dfc12f6-a197-401a-b3f9-c5d34032ae98 · outbound

This paper cites 2015 Computing in Cardiology Conference (CinC) , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2015 Computing in Cardiology Conference (CinC) , pages=

Reference 63

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source=arxiv_source observed=2026-08-01T11:14:30.635105Z digest=sha256:d509bc11b36f1cf41547da73621b1a143f134ba9b1a1666b0a039317fc610afa

Observation 579cf039-eeec-4b80-b1ad-f3369c342997 · outbound

This paper cites A new approach for open-end sequential change point monitoring.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python A new approach for open-end sequential change point monitoring

Reference 64

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source=arxiv_source observed=2026-08-01T11:14:30.705793Z digest=sha256:545379d785cf17e0f3365dc34c76aff6e7726e4c1733b57cced9d66303d2e358

Observation 4d2ebd92-eede-4c2a-9f69-bcd91e52d524 · outbound

This paper cites Real Time Anomaly Detection And Categorisation.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Real Time Anomaly Detection And Categorisation

Reference 65

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source=arxiv_source observed=2026-08-01T11:14:30.830166Z digest=sha256:b8c886d49f14694400ce21193bdaf88371024f5e9ded478d5984b1914f27d274

Observation 4ad979ba-ab96-468c-96fa-30e7626129c8 · outbound

This paper cites Conformalized density- and distance-based anomaly detection in time-series data.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Conformalized density- and distance-based anomaly detection in time-series data

Reference 66

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source=arxiv_source observed=2026-08-01T11:14:30.997923Z digest=sha256:9347c095bc32e98591ea8ffa32a6e7c3f1b5f384f60540cc02ba4a70f9c5ca81

Observation 57c33e06-a5ab-423d-a9c7-38b94a903f9d · outbound

This paper cites Econometrica: Journal of the Econometric Society , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Econometrica: Journal of the Econometric Society , pages=

Reference 67

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source=arxiv_source observed=2026-08-01T11:14:31.093511Z digest=sha256:0ac0435fba280020e81b67b76bb4f6eaa384ab4bf8c76886b21da5c63966b8ad

Observation e61646d6-5039-466c-828e-608db310ace7 · outbound

This paper cites 2010 , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2010 , pages=

Reference 68

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source=arxiv_source observed=2026-08-01T11:14:31.155445Z digest=sha256:193de16719ef6f014713bbc9b02057e1a9defaedd8c365878c8a479156c2bb29

Observation fc13865e-f024-43e7-af7f-0ac2f9b34370 · outbound

This paper cites Mathematics and computers in simulation , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematics and computers in simulation , volume=

Reference 69

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source=arxiv_source observed=2026-08-01T11:14:31.342243Z digest=sha256:cdac7097c8f43083e43bea2e5717d11ac504063d3300f9ae45a2087c7434c601

Observation 2d94fcf9-5a94-432b-878b-d5c0a5fc919d · outbound

This paper cites Journal of Statistical Planning and Inference , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Planning and Inference , volume=

Reference 70

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:31.460781Z digest=sha256:5d331744e1c7b09eb7e9b6d0c946c367b728b5f346dd4014713657d1b63a6678

Observation 431a0fb8-b7c3-47b3-9ef1-5be2caaceeef · outbound

This paper cites Biometrika , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=

Reference 71

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:31.614503Z digest=sha256:db7562eb4ad64b04d90fdba6959bbd444c289b02bd8d7783b9ca3e43e7ac7499

Observation 47f13838-2646-4298-9ee1-054a8e793136 · outbound

This paper cites Technometrics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Technometrics , volume=

Reference 72

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source=arxiv_source observed=2026-08-01T11:14:31.731072Z digest=sha256:2dccd3af703612cbac42c9b912d236a7c28e943b2b603e5175dadb6c78acea88

Observation 3314e33d-aed3-48ea-96d4-5dee33ebaaae · outbound

This paper cites 2010 , publisher=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2010 , publisher=

Reference 73

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:31.870709Z digest=sha256:43e552d908d95a4251ecbd719a82f6f51b322dbb2a3cdba67b6dfb9e119db53f

Observation e96c185b-0ac4-4f7c-81cf-580eb06793e4 · outbound

This paper cites IEEE Transactions on signal processing , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Transactions on signal processing , volume=

Reference 74

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:32.028003Z digest=sha256:afb81791430b871a77f9fcc5922b4ddd80d444191dd9792819ff4eb5da310aa1

Observation 47b050aa-a1f3-4a88-9362-ca1fc1eb5589 · outbound

This paper cites International conference on research in networking , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python International conference on research in networking , pages=

Reference 75

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source=arxiv_source observed=2026-08-01T11:14:32.142280Z digest=sha256:1f00a6bf9d91bedb436649e5e89c5aae27e0e12c2905f917127f74bb12ab3889

Observation 84c6c547-1977-4ef0-9536-c7677e1245c5 · outbound

This paper cites Renewable and Sustainable energy reviews , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Renewable and Sustainable energy reviews , volume=

Reference 76

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:32.260920Z digest=sha256:6e7871d7703695a0531c2c94177ebc15171616fc5137a8a952b9954b354c150b

Observation 3cac8f84-a1f3-4c4e-9b36-2038883b494c · outbound

This paper cites 2013 , publisher=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , publisher=

Reference 77

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source=arxiv_source observed=2026-08-01T11:14:32.396613Z digest=sha256:eba987255cb9758aac7beb1fc75d238162ff526fee3c73e5dbfdecebc746784a

Observation eeb12b3e-ac7d-42a6-b873-e8fabaadf6fc · outbound

This paper cites Mechanical Systems and Signal Processing , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mechanical Systems and Signal Processing , volume=

Reference 78

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:14:32.546982Z digest=sha256:d73543b70790fd32476d7e278fe0e2e26e16a2a111232d3fa4ae15f30b38ec34

Observation 9f9edbad-193c-49b7-9ef2-5af51bce67db · outbound

This paper cites IEEE Control Systems Magazine , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Control Systems Magazine , volume=

Reference 79

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source=arxiv_source observed=2026-08-01T11:14:32.656191Z digest=sha256:fda2c22a55d58229736c20ac7980751e919f5765809b43c489eda4f9e80870a5

Observation f9dc814a-35fb-4081-acdb-ceadc99d7950 · outbound

This paper cites Monthly Notices of the Royal Astronomical Society , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Monthly Notices of the Royal Astronomical Society , volume=

Reference 80

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Observation 451505d8-effc-4433-9622-79f9517e00a0 · outbound

This paper cites 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID) , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID) , pages=

Reference 81

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Observation 462a0d59-84ba-4cb7-9cfc-e7370d546277 · outbound

This paper cites Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , volume=

Reference 82

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Observation 24e22cca-38c7-45d9-a071-0754162b7918 · outbound

This paper cites Mathematical finance—Bachelier congress 2000 , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematical finance—Bachelier congress 2000 , pages=

Reference 83

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source=arxiv_source observed=2026-08-01T11:14:33.057926Z digest=sha256:0f8459df53c1520fd117a3bd1ef79b335c18dbdd95fd33cc32fef648904f41be

Observation 9a4432a4-8776-4594-a02c-3577413b204c · outbound

This paper cites 2019 IEEE International Symposium on Information Theory (ISIT) , pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2019 IEEE International Symposium on Information Theory (ISIT) , pages=

Reference 84

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source=arxiv_source observed=2026-08-01T11:14:33.133870Z digest=sha256:25d74fe2a202b6e7e391ec5f3c67c42e6d3d37bbcc97d73b96218d231437b3dc

Observation 3061dcb2-64e6-4307-8862-e32d3bd4a871 · outbound

This paper cites New procedure for change detection operating on R.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python New procedure for change detection operating on R

Reference 85

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source=arxiv_source observed=2026-08-01T11:14:33.242898Z digest=sha256:9f4effd99d96ae2eeb84f9dddf21b26bdec60e5c2cf02b4cfec413c4eea509a5

Observation cf34fd53-a8b5-4724-bdcf-71de16c4eb48 · outbound

This paper cites 2011 , publisher=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2011 , publisher=

Reference 86

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source=arxiv_source observed=2026-08-01T11:14:33.314005Z digest=sha256:c3bb1a8cbb3233a18b14e015e9222bce54ae29f2760e56e0a63717cff4270aaa

Observation 69a1544c-f3d6-437a-9a48-e8c90ae8acbd · outbound

This paper cites Bioinformatics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Bioinformatics , volume=

Reference 87

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source=arxiv_source observed=2026-08-01T11:14:33.410919Z digest=sha256:673633aecfd2c278fe836633ea846ba9a17bddf0ff86e1274993da68c5104fa3

Observation 1846418a-8562-4720-8346-f70b1063ea03 · outbound

This paper cites Press, Princeton, NJ , year=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Press, Princeton, NJ , year=

Reference 88

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source=arxiv_source observed=2026-08-01T11:14:33.600341Z digest=sha256:307d2bfa5836438f4f265a196c5d11ce2246b15b2542e2a3ae152826139fe6ec

Observation 28b7f0aa-152b-40fe-a297-a6eb5f97ac65 · outbound

This paper cites and Ewans, Kevin and Jonathan, Philip , issn =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Ewans, Kevin and Jonathan, Philip , issn =

Reference 89

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source=arxiv_source observed=2026-08-01T11:14:33.740883Z digest=sha256:8c8506f3ed2346d646a0e2f570d913a522d281dcda14202a9fe898d04d4a5b66

Observation 261ac1d8-602a-4426-836f-ed82db97227f · outbound

This paper cites and Lund, Robert and Lu, Qi Qi , doi =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Lund, Robert and Lu, Qi Qi , doi =

Reference 90

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source=arxiv_source observed=2026-08-01T11:14:33.900967Z digest=sha256:287b10adeeeea3b9863ac9d27c0fe903008ef9de074ac82543b98456cd39a8f6

Observation c082107f-8d2d-40c3-99ac-4ec97dd03b2c · outbound

This paper cites Biostatistics , month = oct, pages =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biostatistics , month = oct, pages =

Reference 91

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source=arxiv_source observed=2026-08-01T11:14:34.030811Z digest=sha256:d8a462f49084db5f3adeb8c32fcd39845b19b4c517ed387fb2d8653ebd824ff0

Observation 855b97b7-a1f6-461c-9cba-9282d37f1d65 · outbound

This paper cites Journal of statistical software , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of statistical software , volume=

Reference 92

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source=arxiv_source observed=2026-08-01T11:14:34.175738Z digest=sha256:9c0d0784d81907251016b1157e589b66d26de74d48fdc15efafa9bbe3394c9b3

Observation 33688a76-59a2-42c8-8f5c-082a1fc64dc4 · outbound

This paper cites Killick and P.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Killick and P

Reference 93

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source=arxiv_source observed=2026-08-01T11:14:34.282431Z digest=sha256:8b9bbc32a645cf7f8a882e21cf4beeaf864c11932bf3de631f7b67cb052f5503

Observation 0992a900-7656-44b7-90ef-666305534990 · outbound

This paper cites 2013 , vol=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , vol=

Reference 94

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source=arxiv_source observed=2026-08-01T11:14:34.320557Z digest=sha256:07de26a4424c09c61f8568b8f545d37ecacf376a12ab09ab871510fe4ed9d9b7

Observation b9aa36c1-cd25-4ab6-8673-67996fbc3e70 · outbound

This paper cites The Annals of Statistics , volume=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python The Annals of Statistics , volume=

Reference 95

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source=arxiv_source observed=2026-08-01T11:14:34.355875Z digest=sha256:b3bf5353069d6eb524b1a688c23b7a556c7806683abf4b7a580cd81a09a7d4ef

Observation a282727c-dd5f-4d7f-894a-ec88166c1950 · outbound

This paper cites 2006 , publisher=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2006 , publisher=

Reference 96

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source=arxiv_source observed=2026-08-01T11:14:34.395870Z digest=sha256:8dc33d1d218c0f2e71c7b2b65b096ffedad9e49364ff70a3b517e4a7b3c48ec1

Observation 16b6d950-d85e-4f3e-879f-15ed4f0f7ede · outbound

This paper cites Journal of the Royal Statistical Society: Series B , number =.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of the Royal Statistical Society: Series B , number =

Reference 97

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source=arxiv_source observed=2026-08-01T11:14:34.441862Z digest=sha256:16db17d46bd1632f243d8d9d76939f51eca1e239fc0133ef533a3784c87c09bf

Observation 6c416a02-054f-45d8-8679-813951247f4e · outbound

This paper cites The Annals of Statistics , year=2000, number=5, volume=28, pages=.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python The Annals of Statistics , year=2000, number=5, volume=28, pages=

Reference 98

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source=arxiv_source observed=2026-08-01T11:14:34.481380Z digest=sha256:02e649868999f19b6d2af5e43e968229934802c36618ca3adecc3f880712a278

Observation 4f615224-8771-45f6-8443-2425a7a8ce0b · outbound

This paper cites an unresolved cited work.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Unresolved cited work

Reference 99

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source=arxiv_source observed=2026-08-01T11:14:34.544749Z digest=sha256:eb2ad3cedcf9a480e00197d5049f726da3ae9c7ef9c1bf8cda7a7bf94dad6749

Observation de6f963f-9790-4131-8d16-ff905c1949a9 · outbound

This paper cites Sequential Tests of Statistical Hypotheses.

focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential Tests of Statistical Hypotheses

Reference 100

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source=arxiv_source observed=2026-08-01T11:14:34.600241Z digest=sha256:83cf9f86eb82a0ac727851feb06868fef636ffb76e8e235d4e9de55bf5c9b856

Pith citing papers

No inbound Pith citation observations are available.