Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T11:14:34.600241Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T11:14:34.600241Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 234 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a7ac90ce-c5a2-41b3-9a73-603edbbf6758 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Killick, Rebecca , year =
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Software , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Romano, Gaetano , year =
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Bayesian Online Changepoint Detection
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematica Scandinavica , pages=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Some minorants and majorants of random walks and L
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Procedures for Reacting to a Change in Distribution
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Observation ecabb8fc-8f6c-4b50-93f3-834092e06ee7 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Ross and Niall M
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Observation 5031e815-c7c3-4f6a-8e26-63854215bb96 · outbound
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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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Scott , title =
Reference 19
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Hawkins and Qiqi Deng , title =
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Observation 75ce09cd-3dbc-40a2-887b-0355b26a5bd1 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Ross and Dimitris K
Reference 21
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python and Tartakovsky, Alexander G
Reference 22
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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
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
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Reference 25
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=
Reference 26
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Signal Process
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Signal processing , volume=
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Observation 19d2c06c-b962-40b0-8e0f-aeb4f26fa74c · outbound
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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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
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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Observation 12439745-3b74-4c27-a7d2-d319ed7c5c35 · outbound
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
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
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
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
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
focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2014 , publisher=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , publisher=
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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
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
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=
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Observation 3a3a0606-d2b5-4e6f-a4d8-877488ffa3c6 · outbound
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
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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Observation 7282fc11-93a0-4f9b-98f3-d649676bba82 · outbound
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
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Software , author=
Reference 46
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Observation 7fec4e0b-893f-4e35-b60e-e40c9bc82d0b · outbound
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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focus and focus-cpt: Fast Online Changepoint Detection in R and Python ruptures: change point detection in Python
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2020 , note =
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Information Processing Letters , volume=
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Observation 9753fbe6-bf15-4457-bab8-086d9929d1b3 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Electronic Journal of Statistics , volume=
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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
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Observation 7e49a87a-d4e7-40d8-9613-1e8c669ad15f · outbound
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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Observation a146e28b-c78b-4572-81e6-eef486c096ed · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Neurocomputing , volume=
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Observation 53bf3af8-725c-489d-9c8a-6a7fc158e50f · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Neural computation , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of the American Statistical Association , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential Analysis , volume=
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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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Observation 1225243c-40a5-4e5c-961b-3f2d748993da · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=
Reference 60
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Transactions on Information Theory , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=
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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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Observation 579cf039-eeec-4b80-b1ad-f3369c342997 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python A new approach for open-end sequential change point monitoring
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Real Time Anomaly Detection And Categorisation
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Observation 4ad979ba-ab96-468c-96fa-30e7626129c8 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Conformalized density- and distance-based anomaly detection in time-series data
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Econometrica: Journal of the Econometric Society , pages=
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Reference 68
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematics and computers in simulation , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of Statistical Planning and Inference , volume=
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Observation 431a0fb8-b7c3-47b3-9ef1-5be2caaceeef · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biometrika , volume=
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Technometrics , volume=
Reference 72
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Observation 3314e33d-aed3-48ea-96d4-5dee33ebaaae · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2010 , publisher=
Reference 73
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Transactions on signal processing , volume=
Reference 74
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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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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Renewable and Sustainable energy reviews , volume=
Reference 76
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Observation 3cac8f84-a1f3-4c4e-9b36-2038883b494c · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , publisher=
Reference 77
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mechanical Systems and Signal Processing , volume=
Reference 78
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Observation 9f9edbad-193c-49b7-9ef2-5af51bce67db · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python IEEE Control Systems Magazine , volume=
Reference 79
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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
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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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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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Mathematical finance—Bachelier congress 2000 , pages=
Reference 83
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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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Observation 3061dcb2-64e6-4307-8862-e32d3bd4a871 · outbound
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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focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2011 , publisher=
Reference 86
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Observation 69a1544c-f3d6-437a-9a48-e8c90ae8acbd · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Bioinformatics , volume=
Reference 87
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focus and focus-cpt: Fast Online Changepoint Detection in R and Python Press, Princeton, NJ , year=
Reference 88
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Observation 28b7f0aa-152b-40fe-a297-a6eb5f97ac65 · outbound
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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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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Observation c082107f-8d2d-40c3-99ac-4ec97dd03b2c · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Biostatistics , month = oct, pages =
Reference 91
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Observation 855b97b7-a1f6-461c-9cba-9282d37f1d65 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Journal of statistical software , volume=
Reference 92
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Observation 33688a76-59a2-42c8-8f5c-082a1fc64dc4 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Killick and P
Reference 93
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Observation 0992a900-7656-44b7-90ef-666305534990 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2013 , vol=
Reference 94
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Observation b9aa36c1-cd25-4ab6-8673-67996fbc3e70 · outbound
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Reference 95
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Observation a282727c-dd5f-4d7f-894a-ec88166c1950 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python 2006 , publisher=
Reference 96
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Observation 16b6d950-d85e-4f3e-879f-15ed4f0f7ede · outbound
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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Observation 6c416a02-054f-45d8-8679-813951247f4e · outbound
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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Observation 4f615224-8771-45f6-8443-2425a7a8ce0b · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Unresolved cited work
Reference 99
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Observation de6f963f-9790-4131-8d16-ff905c1949a9 · outbound
focus and focus-cpt: Fast Online Changepoint Detection in R and Python Sequential Tests of Statistical Hypotheses
Reference 100
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No inbound Pith citation observations are available.