Compute discrete wavelets.

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Description

For a given wavelet computes a list with each entry of the list containing that discrete wavelet at a different scale. The first entry corresponds to the finest wavelet, the next entry to the next finest, and so on.

Usage

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mkcoef(J, filter.number = 10, family = "DaubLeAsymm")

Arguments

J

A NEGATIVE integer. -J is the maximum number of levels to compute.

filter.number

The filter number (number of vanishing moments) of the underlying wavelet to use.

family

The family of the wavelet. See wd help for further info.

Value

A list of length J. The first entry contains the discrete wavelet at the finest scale, the 2nd entry contains the next most finest wavelet, and so on.

Author(s)

Guy Nason.

References

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.

See Also

Rvarlacf, whichlevel

Examples

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#
# E.g. compute discrete Haar wavelets on scales 1, 2, 3.
#
mkcoef(-3, 1, "DaubExPhase")
#[[1]]
#[1]  0.7071068 -0.7071068
#
#[[2]]
#[1]  0.5  0.5 -0.5 -0.5
#
#[[3]]
#[1]  0.3535534  0.3535534  0.3535534  0.3535534 -0.3535534 -0.3535534 -0.3535534
#[8] -0.3535534

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