Dynamic harmonic regression

@inproceedings{Young1999DynamicHR,
  title={Dynamic harmonic regression},
  author={Peter C. Young and D. J. Pedregal and Wlodek Tych},
  year={1999}
}
This paper describes in detail a flexible approach to nonstationary time series analysis based on a Dynamic Harmonic Regression (DHR) model of the Unobserved Components (UC) type, formulated within a stochastic state space setting. The model is particularly useful for adaptive seasonal adjustment, signal extraction and interpolation over gaps, as well as forecasting or backcasting. The Kalman Filter and Fixed Interval Smoothing algorithms are exploited for estimating the various components… CONTINUE READING

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