A wavelet-based time-varying autoregressive model for non-stationary and irregular time series

In this work we propose an autoregressive model with parameters varying in time applied to irregularly spaced non-stationary time series. We expand all the functional parameters in a wavelet basis and estimate the coefficients by least squares after truncation at a suitable resolution level. We also...

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Veröffentlicht in:	Journal of applied statistics 2012-11, Vol.39 (11), p.2313-2325
Hauptverfasser:	Salcedo, G. E., Porto, R. F., Roa, S. Y., Momo, F. R.
Format:	Artikel
Sprache:	eng
Schlagworte:	autoregressive model irregularly spaced time series locally stationary processes multiresolution analysis Parameter estimation Regression analysis Simulation Studies Time series Wavelet transforms wavelets
Online-Zugang:	Volltext
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