Detection of periodicity based on independence tests - III. Phase distance correlation periodogram

Shay Zucker*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


I present the Phase Distance Correlation (PDC) periodogram - a new periodicity metric, based on the Distance Correlation concept of Gábor Székely. For each trial period, PDC calculates the distance correlation between the data samples and their phases. PDC requires adaptation of the Székely's distance correlation to circular variables (phases). The resulting periodicity metric is best suited to sparse data sets, and it performs better than other methods for sawtoothlike periodicities. These include Cepheid and RR-Lyrae light curves, as well as radial velocity curves of eccentric spectroscopic binaries. The performance of the PDC periodogram in other contexts is almost as good as that of the Generalized Lomb-Scargle periodogram. The concept of phase distance correlation can be adapted also to astrometric data, and it has the potential to be suitable also for large evenly spaced data sets, after some algorithmic perfection.

Original languageEnglish
Pages (from-to)L86-L90
JournalMonthly Notices of the Royal Astronomical Society: Letters
Issue number1
StatePublished - 1 Feb 2018


FundersFunder number
Israel Science Foundation848/16


    • Binaries: spectroscopic
    • Methods: data analysis
    • Methods: statistical
    • Stars: variables: Cepheids
    • Stars: variables: RR Lyrae


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