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Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems, 2017-10, Vol.20 (3), p.275-290
Circular autocorrelation of stationary circular Markov processes
Ist Teil von
Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems, 2017-10, Vol.20 (3), p.275-290
Ort / Verlag
Dordrecht: Springer Netherlands
Erscheinungsjahr
2017
Quelle
SpringerLink
Beschreibungen/Notizen
The stationary Markov process is considered and its circular autocorrelation function is investigated. More specifically, the transition density of the stationary Markov circular process is defined by two circular distributions, and we elucidate the structure of the circular autocorrelation when one of these distributions is uniform and the other is arbitrary. The asymptotic properties of the natural estimator of the circular autocorrelation function are derived. Furthermore, we consider the bivariate process of trigonometric functions and provide the explicit form of its spectral density matrix. The validity of the model was assessed by applying it to a series of wind direction data.