The Lomb-Scargle periodogram was introduced in astrophysics to detect sinusoidal
signals in noisy unevenly sampled time series. It proved to be a powerful tool in
time series analysis and has recently been adapted in biomedical sciences. Its use
is motivated by handling non-uniform data which is a common characteristic due
to the restricted and irregular observations of, for instance, free-living animals.
However, the observational data often contain fractions of non-Gaussian noise or
may consist of periodic signals with non-sinusoidal shapes. These properties can
make more difficult the interpretation of Lomb-Scargle periodograms and can lead
to misleading estimates. In this letter we illustrate these difficulties for noise-free
bimodal rhythms and sinusoidal signals with outliers. The examples are aimed to
emphasize limitations and to complement the recent discussion on Lomb-Scargle
periodograms.The author is grateful to Mirian D. Marques for critical reading of the manuscript and
financial support by the FAPESP (Fundação de Amparo à Pesquisa do Estado de São
Paulo) grant 97/04780-6.Peer reviewe