Statistical Properties of Solar Flare Dependency
Conference: Symposium on Data Science and Statistics (SDSS) 2023
05/26/2023: 10:35 AM - 10:40 AM CDT
Lightning
As machine learning methods become more prevalent within the solar flare prediction community, a complete understanding of the distributions which govern the flare process is needed for appropriate statistical modeling. In order to analyze the dependency structure that subsequent flares exhibit, we adopt the use of hypothesis testing to identify time intervals which flaring events are highly dependent as well as time intervals where they appear to be independent events. Information from this analysis could be implemented to improve operational solar flare prediction systems where forecasts are constantly updated with the most up to date information.
Astrostatistics
Solar flares
Presenting Author
Noah Kochanski, University of Michigan
First Author
Noah Kochanski, University of Michigan
CoAuthor
Yang Chen, University of Michigan
Target Audience
Beginner
Tracks
Practice and Applications
Symposium on Data Science and Statistics (SDSS) 2023
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