
dwpt(x, wf="la8", n.levels=4, boundary="periodic")
idwpt(y, y.basis)
modwpt(x, wf = "la8", n.levels = 4, boundary = "periodic")
"la8"
, the Daubechies orthonormal compactly
supported wavelet of length $L=8$ (Daubechies, 1992), least
asymmetric family.boundary=="periodic"
the default, then the vector you
decompose is assumed to be periodic on its defined interval,
if boundary=="reflection"
, the vector beyond its Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
Wickerhauser, M. V. (1994) Adapted Wavelet Analysis from Theory to Software, A K Peters.
dwt
, modwpt
, wave.filter
.data(mexm)
J <- 4
mexm.mra <- mra(log(mexm), "mb8", J, "modwt", "reflection")
mexm.nomean <- ts(
apply(matrix(unlist(mexm.mra), ncol=J+1, byrow=FALSE)[,-(J+1)], 1, sum),
start=1957, freq=12)
mexm.dwpt <- dwpt(mexm.nomean[-c(1:4)], "mb8", 7, "reflection")
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