Nonparametric Inference for Periodic Sequences Academic Article uri icon


  • This article proposes a nonparametric method for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both theoretically and by simulation.We also propose a nonparametric test of the null hypothesis that the data have constantmean against the alternative that the sequence of means is periodic. Finally, our methodology is demonstrated on three well-known time series: the sunspots and lynx trapping data, and the El Nio series of sea surface temperatures. 2012 American Statistical Association and the American Society for Quality.

published proceedings


author list (cited authors)

  • Sun, Y., Hart, J. D., & Genton, M. G.

citation count

  • 10

complete list of authors

  • Sun, Ying||Hart, Jeffrey D||Genton, Marc G

publication date

  • January 2012