Rare Event Classification with Weighted Logistic Regression for Identifying Repeating Fast Radio Bursts

Rare Event Classification with Weighted Logistic Regression for Identifying Repeating Fast Radio Bursts

An important task in the study of fast radio bursts (FRBs) remains the automatic classification of repeating and nonrepeating sources based on their morphological properties. We propose a statistical model that considers a modified logistic regression to classify FRB sources. The classical logistic...

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Bibliographic Details
Main Authors: Antonio Herrera-Martin, Radu V. Craiu, Gwendolyn M. Eadie, David C. Stenning, Derek Bingham, B. M. Gaensler, Ziggy Pleunis, Paul Scholz, Ryan Mckinven, Bikash Kharel, Kiyoshi W. Masui
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal
Subjects:
Radio transient sources
Classification
Astrostatistics techniques
Sampling distribution
Astrostatistics distributions
Regression
Online Access:https://doi.org/10.3847/1538-4357/adb623
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https://doi.org/10.3847/1538-4357/adb623

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