wt: Compute wavelet transform

In tgouhier/biwavelet: Conduct Univariate and Bivariate Wavelet Analyses

Compute wavelet transform

Description

Compute wavelet transform

Usage

wt(
  d,
  pad = TRUE,
  dt = NULL,
  dj = 1/12,
  s0 = 2 * dt,
  J1 = NULL,
  max.scale = NULL,
  mother = "morlet",
  param = -1,
  lag1 = NULL,
  sig.level = 0.95,
  sig.test = 0,
  do.sig = TRUE,
  arima.method = "CSS"
)

Arguments

d	Time series in matrix format (n rows x 2 columns). The first column should contain the time steps and the second column should contain the values.
pad	Pad the values will with zeros to increase the speed of the transform.
dt	Length of a time step.
dj	Spacing between successive scales.
s0	Smallest scale of the wavelet.
J1	Number of scales - 1.
max.scale	Maximum scale. Computed automatically if left unspecified.
mother	Type of mother wavelet function to use. Can be set to morlet, dog, or paul.
param	Nondimensional parameter specific to the wavelet function.
lag1	AR(1) coefficient of time series used to test for significant patterns.
sig.level	Significance level.
sig.test	Type of significance test. If set to 0, use a regular \chi^2 test. If set to 1, then perform a time-average test. If set to 2, then do a scale-average test.
do.sig	Perform significance testing if TRUE.
arima.method	Fitting method. This parameter is passed as the method Parameter to the arima function.

Value

Returns a biwavelet object containing:

coi	matrix containg cone of influence
wave	matrix containing the wavelet transform
power	matrix of power
power.corr	matrix of bias-corrected power using the method described by Liu et al. (2007)
phase	matrix of phases
period	vector of periods
scale	vector of scales
dt	length of a time step
t	vector of times
xaxis	vector of values used to plot xaxis
s0	smallest scale of the wavelet
dj	spacing between successive scales
sigma2	variance of time series
mother	mother wavelet used
type	type of biwavelet object created (wt)
signif	matrix containg significance levels

Author(s)

Tarik C. Gouhier ([e-mail])

Code based on wavelet MATLAB program written by Christopher Torrence and Gibert P. Compo.

References

Torrence, C., and G. P. Compo. 1998. A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society 79:61-78.

Liu, Y., X. San Liang, and R. H. Weisberg. 2007. Rectification of the Bias in the Wavelet Power Spectrum. Journal of Atmospheric and Oceanic Technology 24:2093-2102.

Examples

t1 <- cbind(1:100, rnorm(100))

## Continuous wavelet transform
wt.t1 <- wt(t1)

## Plot power
## Make room to the right for the color bar
par(oma = c(0, 0, 0, 1), mar = c(5, 4, 4, 5) + 0.1)
plot(wt.t1, plot.cb = TRUE, plot.phase = FALSE)

tgouhier/biwavelet documentation built on Aug. 9, 2024, 7:36 a.m.