  Examples of cyclic (periodic) behavior in geophysical data abound. In many
cases the primary period is known, such as in daily measurements of rain,
temperature, and sea level. However, many time series of measurements contain
cycles of unknown or varying length. We consider the problem of estimating the
unknown period in a time series.We review the basic methods, compare their
performance through a simulation studyusing observed sea level data, apply them
to an astronomical data set, and discuss generalizations of the methods.
