The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
FLEXIBLE AND SCALABLE METHODS FOR QUANTIFYING STOCHASTIC VARIABILITY IN THE ERA OF MASSIVE TIME-DOMAIN ASTRONOMICAL DATA SETS
Open accessAbstract
We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.
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Self-citationIntroduction to Time Series and Forecasting
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FIRST RESULTS FROM THE CATALINA REAL-TIME TRANSIENT SURVEY
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Understanding the Lomb–Scargle Periodogram
VanderPlas, J. T. (2018) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/aab766 · Cited by 1,248
Active galactic nuclei: what’s in a name?
Padovani, P., Alexander, D. M., Assef, R. J., De Marco, B., Giommi, P., Hickox, R. C., Richards, G. T., Smolčić, V., Hatziminaoglou, E., Mainieri, V., et al. (2017) · The Astronomy and Astrophysics Review · doi:10.1007/s00159-017-0102-9 · Cited by 666
PERIODOGRAMS FOR MULTIBAND ASTRONOMICAL TIME SERIES
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THE SLOAN DIGITAL SKY SURVEY REVERBERATION MAPPING PROJECT: TECHNICAL OVERVIEW
Shen, Y., Brandt, W. N., Dawson, K. S., Hall, P. B., McGreer, I. D., Anderson, S. F., Chen, Y., Denney, K. D., Eftekharzadeh, S., Fan, X., et al. (2014) · The Astrophysical Journal Supplement Series · doi:10.1088/0067-0049/216/1/4 · Cited by 210
Self-citation
Metadata
- Authors
- Kelly, B. C., Becker, A. C., Sobolewska, M., Siemiginowska, A., & Uttley, P.
- Venue
- The Astrophysical Journal
- Publisher
- American Astronomical Society
- Published
- 2014-05-19
- Volume
- 788
- Issue
- 1
- Pages
- 33
- ISSN
- 0004-637X (ISSN-L)
- 1538-4357
- OpenAlex
- W2017719162
- Cited by
- 270
- References
- 51
- FWCI
- 8.00
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kelly, B. C., Becker, A. C., Sobolewska, M., Siemiginowska, A., & Uttley, P. (2014). FLEXIBLE AND SCALABLE METHODS FOR QUANTIFYING STOCHASTIC VARIABILITY IN THE ERA OF MASSIVE TIME-DOMAIN ASTRONOMICAL DATA SETS. The Astrophysical Journal. https://doi.org/10.1088/0004-637x/788/1/33
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