Phase dispersion minimization methods for estimation of periods from unequally spaced sequences of data

Details Phase dispersion minimization methods for estimation of periods from unequally spaced sequences of data Phase dispersion minimization methods for estimation of periods from unequally spaced sequences of data

Nov 1983

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1983esasp.201...37p&link_type=abstract

In ESA Statist. Methods in Astron. p 37-42 (SEE N84-19196 09-89)

Statistics

13

Fourier Transformation, Least Squares Method, Periodic Variations, Stellar Spectrophotometry, Time Series Analysis, Optimization, Periodic Functions, Run Time (Computers)

Scientific paper

There are three well-known families of period estimation methods for uneven sequences of observations: Fourier transform methods, least-squares estimation methods and phase dispersion minimization methods. For simple harmonic waveforms all three methods give essentially equivalent results. However, for more complicated waveforms (and this is the rule for astronomical data) differences arise. The author tries to demonstrate that the phase dispersion methods generally outperform the others. It is possible to construct more sensitive statistics than with Fourier transform methods. For least-squares methods, the point of difference is the execution time of related computer programs. Moreover, the phase dispersion methods can be used to simulate the other two.

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