spec.wave(x, wavelet="s8", n.levels=6, shrink.level=NULL, detrend=T, plot=T, shrink.fun="soft", taper=.1)
"d4", "s8"
.
See
wavelet
for a list of all available wavelet names.
n.levels
is bigger than
ml
, where
ml
is the maximum possible level,
computed from the
max.level
function, then
n.levels
is set to
ml
and
a warning message is given.
n.levels-1
.
TRUE
, remove a least squares line from the time series before computing
periodogram.
TRUE
, a plot of the spectrum will be provided. See
spec.plot
for
details.
soft
and
hard
, default is
soft
. See
shrink
for
details.
spec.pgram
for details.
10*log10(power)
).
WaveShrink
" followed by the filter name used in the analysis
and
shrink.level
.
Zeros are padded at the beginning of the original time series to make the
series length divisible by
2^(n.levels)
.
Thresholds are computed based on Gao (1993).
Gao, Hong-Ye (1993). Wavelet Shrinkage Estimates of Spectrum in Time Series.
ma.1 <- arima.sim(model=list(ma=1), n=512) # MA Example par(mfrow=c(2,2)) plot((1:200)/400, log(4)+2*log(sin(pi*(1:200)/800)), type="l", xlab="frequency", ylab="spectrum", main="True Spectrum") ma.raw <- spectrum(ma.1) # raw periodogram ma.ar <- spectrum(ma.1, "ar") # AR estimate ma.wave <- spec.wave(ma.1, "s10", shrink.level=5) # waveshrink estimate