ewspecHaarNonPer | R Documentation |
This function uses the special HwdS
function
to compute the Haar wavelet transform with out boundary
conditions (neither periodic, interval, mirror reflection).
This is so all coefficients are genuine Haar coefficients without
involving extra/repeated data.
ewspecHaarNonPer(x, filter.number = 1, family = "DaubExPhase",
UseLocalSpec = TRUE, DoSWT = TRUE, WPsmooth = TRUE,
verbose = FALSE, smooth.filter.number = 10,
smooth.family = "DaubLeAsymm",
smooth.levels = 3:WPwst$nlevels - 1, smooth.dev = madmad,
smooth.policy = "LSuniversal", smooth.value = 0,
smooth.by.level = FALSE, smooth.type = "soft",
smooth.verbose = FALSE, smooth.cvtol = 0.01,
smooth.cvnorm = l2norm, smooth.transform = I,
smooth.inverse = I)
x |
A vector of dyadic length that contains the time series you want to form the EWS of. |
filter.number |
Should always be 1 (for Haar) |
family |
Should always be "DaubExPhase", for Haar. |
UseLocalSpec |
Should always be |
DoSWT |
Should always be |
WPsmooth |
Should alway be |
verbose |
If |
smooth.filter.number |
Wavelet filter number for doing the wavelet smoothing of the EWS estimate. |
smooth.family |
Wavelet family for doing the wavelet smoothing of the EWS estimate. |
smooth.levels |
Which levels of the EWS estimate to apply smoothing to. |
smooth.dev |
What kind of deviance to use. The default is madmad, an alternative might be var. |
smooth.policy |
What kind of smoothing to use. See help
page for |
smooth.value |
If a manual value has to be supplied according
to the |
smooth.by.level |
If |
smooth.type |
The type of wavelet smoothing "hard" or "soft" |
smooth.verbose |
If |
smooth.cvtol |
If cross-validation smoothing is used, this is the tolerance |
smooth.cvnorm |
If cross-validation smoothing used, this is the norm that's used |
smooth.transform |
A transform is applied before smoothing |
smooth.inverse |
The inverse transform is applied after smoothing |
This function is very similar
to ewspec
from wavethresh, and many arguments here perform
the same function as there.
The same value as for the ewspec
function.
Guy Nason.
Nason, G.P. (2013) A test for second-order stationarity and approximate confidence intervals for localized autocovariances for locally stationary time series. J. R. Statist. Soc. B, 75, 879-904. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/rssb.12015")}
hwtos2
,
HwdS
#
# Requires wavethresh, so not run directly in installation of package
#
ewspecHaarNonPer(rnorm(512))
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