Time-varying and Seasonal Analysis Using Hilbert Wavelet Pairs
Performs time-varying or seasonal coherence and phase anlaysis between two time seris using the maximal-overlap discrete Hilbert wavelet transform (MODHWT).
modhwt.coh(x, y, f.length = 0) modhwt.phase(x, y, f.length = 0) modhwt.coh.seasonal(x, y, S = 10, season = 365) modhwt.phase.seasonal(x, y, season = 365)
x |
MODHWT object. |
y |
MODHWT object. |
f.length |
Length of the rectangular filter. |
S |
Number of "seasons". |
season |
Length of the "season". |
The idea of seasonally-varying spectral analysis (SVSA, Madden 1986) is generalized using the MODWT and Hilbert wavelet pairs. For the seasonal case, S seasons are used to produce a consistent estimate of the coherence and phase. For the non-seasonal case, a simple rectangular (moving-average) filter is applied to the MODHWT coefficients in order to produce consistent estimates.
Time-varying or seasonal coherence and phase between two time series. The coherence estimates are between zero and one, while the phase estimates are between -pi and pi.
B. Whitcher
Madden, R.A. (1986). Seasonal variation of the 40–50 day oscillation in the tropics. Journal of the Atmospheric Sciences\/ 43\/(24), 3138–3158.
Whither, B. and P.F. Craigmile (2004). Multivariate Spectral Analysis Using Hilbert Wavelet Pairs, International Journal of Wavelets, Multiresolution and Information Processing, to appear.
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