dplR (version 1.7.6)

morlet: Perform a Continuous Morlet Wavelet Transform

Description

This function performs a continuous wavelet transform on a time series.

Usage

morlet(y1, x1 = seq_along(y1), p2 = NULL, dj = 0.25, siglvl = 0.95)

Value

A list containing:

y

numeric. The original time series.

x

numeric. The time values.

wave

complex. The wavelet transform.

coi

numeric. The cone of influence.

period

numeric. The period.

Scale

numeric. The scale.

Signif

numeric. The significant values.

Power

numeric. The squared power.

Arguments

y1

numeric vector. Series to be transformed.

x1

numeric. A vector of values giving the years for the plot. Must be the same length as length(y1).

p2

numeric. The number of power of two to be computed for the wavelet transform. Calculated from length of y1 if NULL.

dj

numeric. Sub-octaves per octave calculated.

siglvl

numeric. Level for the significance test.

Author

Andy Bunn. Patched and improved by Mikko Korpela.

Details

This performs a continuous wavelet transform of a time series. This function is typically invoked with wavelet.plot.

References

Torrence, C. and Compo, G. P. (1998) A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78.

See Also

wavelet.plot

Examples

library(utils)
data(ca533)
ca533.rwi <- detrend(rwl = ca533, method = "ModNegExp")
ca533.crn <- chron(ca533.rwi, prewhiten = FALSE)
Years <- time(ca533.crn)
CAMstd <- ca533.crn[, 1]
out.wave <- morlet(y1 = CAMstd, x1 = Years, dj = 0.1, siglvl = 0.99)