Derezea, Efthymia, Kume, Alfred, Froebrich, Dirk (2023) An application of Saddlepoint approximation for period detection of stellar light observations. Journal of the Royal Statistical Society Series C: Applied Statistics, 72 (1). pp. 1-19. ISSN 0035-9254. E-ISSN 1467-9876. (doi:10.1093/jrsssc/qlac001) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:100495)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: https://doi.org/10.1093/jrsssc/qlac001 |
Resource title: | An application of Saddlepoint Approximation for period detection of stellar light observations |
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Resource type: | Publication |
URN: | 10.48550/arXiv.2201.11762 |
KDR/KAR URL: | https://kar.kent.ac.uk/98210/ |
External URL: | https://doi.org/10.48550/arXiv.2201.11762 |
Abstract
One of the main features of interest in analysing the light curves of stars is the underlying periodic behaviour. The corresponding observations are a complex type of time series with unequally spaced time points. The main tools for analysing these type of data rely on the periodogram-like functions constructed with a desired feature so that the peaks indicate the presence of a potential period. We explore a particular periodogram for the irregularly observed time series. We identify the potential periods by implementing the saddlepoint approximation, as a faster and more accurate alternative to the simulation based methods that are currently used. The power analysis of the testing methodology is reported together with applications using light curves from the Hunting Outbursting Young Stars citizen science project.
Item Type: | Article |
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DOI/Identification number: | 10.1093/jrsssc/qlac001 |
Uncontrolled keywords: | Statistics, Probability and Uncertainty, Statistics and Probability |
Subjects: |
Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics Q Science > QB Astronomy > QB460 Astrophysics |
Divisions: |
Divisions > Division of Natural Sciences > Physics and Astronomy Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Funders: | University of Kent (https://ror.org/00xkeyj56) |
SWORD Depositor: | JISC Publications Router |
Depositing User: | JISC Publications Router |
Date Deposited: | 13 Apr 2023 13:53 UTC |
Last Modified: | 05 Aug 2024 14:31 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/100495 (The current URI for this page, for reference purposes) |
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