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Poisson-FOCuS on SIGMA data

Research output: Contribution to conference - Without ISBN/ISSN › Speech

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Standard

Poisson-FOCuS on SIGMA data. / Ward, Kes; McGarry, Luke; Pyke, Caroline.
2023.

Research output: Contribution to conference - Without ISBN/ISSN › Speech

Harvard

Ward, K, McGarry, L & Pyke, C 2023, 'Poisson-FOCuS on SIGMA data'. <https://indico.cern.ch/event/731980/contributions/5573915/attachments/2730471/4746516/Kes__Sigma_Data_Challenge%20(6).pdf>

APA

Ward, K., McGarry, L., & Pyke, C. (2023). Poisson-FOCuS on SIGMA data. https://indico.cern.ch/event/731980/contributions/5573915/attachments/2730471/4746516/Kes__Sigma_Data_Challenge%20(6).pdf

Vancouver

Ward K, McGarry L, Pyke C. Poisson-FOCuS on SIGMA data. 2023.

Author

Ward, Kes ; McGarry, Luke ; Pyke, Caroline. / Poisson-FOCuS on SIGMA data.

Bibtex

@conference{8973b4340ff140a0ad846a272f67dbd9,
title = "Poisson-FOCuS on SIGMA data",
abstract = "The Poisson Functional Online Cumulative Sum (Poisson-FOCuS) method is a method for solving the likelihood ratio test of Poisson(λ) null against Poisson(μλ) alternative where μ>1, i.e. searching for an increase in count. This can be thought of as equivalent to testing all possible anomaly start points τ<T at each timestep T, giving a computationally efficient way to analyse count anomalies that occur over intervals of time. We run the Poisson-FOCuS method on SIGMA data, with an additional adjustment to remove anomaly tail traces, and report the results.",
author = "Kes Ward and Luke McGarry and Caroline Pyke",
year = "2023",
month = oct,
day = "9",
language = "English",

}

RIS

TY - CONF

T1 - Poisson-FOCuS on SIGMA data

AU - Ward, Kes

AU - McGarry, Luke

AU - Pyke, Caroline

PY - 2023/10/9

Y1 - 2023/10/9

N2 - The Poisson Functional Online Cumulative Sum (Poisson-FOCuS) method is a method for solving the likelihood ratio test of Poisson(λ) null against Poisson(μλ) alternative where μ>1, i.e. searching for an increase in count. This can be thought of as equivalent to testing all possible anomaly start points τ<T at each timestep T, giving a computationally efficient way to analyse count anomalies that occur over intervals of time. We run the Poisson-FOCuS method on SIGMA data, with an additional adjustment to remove anomaly tail traces, and report the results.

AB - The Poisson Functional Online Cumulative Sum (Poisson-FOCuS) method is a method for solving the likelihood ratio test of Poisson(λ) null against Poisson(μλ) alternative where μ>1, i.e. searching for an increase in count. This can be thought of as equivalent to testing all possible anomaly start points τ<T at each timestep T, giving a computationally efficient way to analyse count anomalies that occur over intervals of time. We run the Poisson-FOCuS method on SIGMA data, with an additional adjustment to remove anomaly tail traces, and report the results.

M3 - Speech

ER -