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dc.contributor.author Talagala, P
dc.date.accessioned 2023-09-20T04:10:30Z
dc.date.available 2023-09-20T04:10:30Z
dc.date.issued 2023-08
dc.identifier.issn 2815-0082 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21434
dc.description.abstract Anomalies play a critical role in statistical analysis, as their presence in data can lead to biased parameter estimation, model misspeci cation, and misleading results if classical analysis techniques are blindly applied. Additionally, anomalies can themselves be carriers of signi cant and critical information, and identifying these critical points can be the primary goal of investigations in many elds such as fraud detection, object tracking, system health monitoring, and environmental monitoring (e.g., for bush res, tsunamis, oods, earthquakes, and volcanic eruptions) en_US
dc.language.iso en en_US
dc.title Unveiling the unusual: a task view for anomaly dection in R en_US
dc.type Article-Full-text en_US
dc.identifier.year 2023 en_US
dc.identifier.journal Bolgoda Plains Research Magazine en_US
dc.identifier.issue 1 en_US
dc.identifier.volume 3 en_US
dc.identifier.pgnos pp. 54-57 en_US
dc.identifier.doi https://doi.org/10.31705/BPRM.v3(1).2023.14 en_US


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