Home > Research > Publications & Outputs > anomalous: Anomaly Detection using the CAPA and...

Research

Links

View graph of relations

anomalous: Anomaly Detection using the CAPA and PELT Algorithms

Research output: Exhibits, objects and web-based outputs › Software

Published

Standard

anomalous: Anomaly Detection using the CAPA and PELT Algorithms. Smith, Paul (Author). 2024.

Research output: Exhibits, objects and web-based outputs › Software

Harvard

Smith, P, anomalous: Anomaly Detection using the CAPA and PELT Algorithms, 2024, Software. <https://doi.org/10.5281/zenodo.14234768>

APA

Smith, P. (2024). anomalous: Anomaly Detection using the CAPA and PELT Algorithms. Software https://doi.org/10.5281/zenodo.14234768

Vancouver

Smith P. anomalous: Anomaly Detection using the CAPA and PELT Algorithms 2024.

Author

Smith, Paul (Author). / anomalous: Anomaly Detection using the CAPA and PELT Algorithms. [Software].

Bibtex

@misc{d5cf653ca99540839a3ebeda0717855c,
title = "anomalous: Anomaly Detection using the CAPA and PELT Algorithms",
abstract = "Flexible implementations in R of the univariate CAPA and PELT algorithms along with various cost functions for different distributions and models. The modular design, using R6 classes, favor ease of extension (for example user written cost functions) over the performance of other implementations (e.g. , ).",
author = "Paul Smith",
year = "2024",
month = dec,
day = "16",
language = "English",

}

RIS

TY - ADVS

T1 - anomalous: Anomaly Detection using the CAPA and PELT Algorithms

AU - Smith, Paul

PY - 2024/12/16

Y1 - 2024/12/16

N2 - Flexible implementations in R of the univariate CAPA and PELT algorithms along with various cost functions for different distributions and models. The modular design, using R6 classes, favor ease of extension (for example user written cost functions) over the performance of other implementations (e.g. , ).

AB - Flexible implementations in R of the univariate CAPA and PELT algorithms along with various cost functions for different distributions and models. The modular design, using R6 classes, favor ease of extension (for example user written cost functions) over the performance of other implementations (e.g. , ).

M3 - Software

ER -