Statistical Models for Time Series of Circular Data

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Data which can be expressed as sets of observations on the circle arise in a number of areas of applications such as meteorology and biology. On occasions, circular observations appear in a time series context. For instance, a series of wind directions measured hourly at a weather station can be considered an example of time series of circular data. Another example is a time series of directions of movements of migratory birds observed in biology. For the modeling of such data, we have proposed some statistical models and investigated their properties. Applications of the models have been given. It has been shown that the presented models provide better fits to some data than the well-known existing processes.