% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/wt.R
\name{wt}
\alias{wt}
\title{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)
}
\arguments{
\item{d}{time series in matrix format (\code{n} rows x 2 columns). The first
column should contain the time steps and the second column should contain
the values.}

\item{pad}{pad the values will with zeros to increase the speed of the
transform. Default is TRUE.}

\item{dt}{length of a time step.}

\item{dj}{spacing between successive scales. Default is 1/12.}

\item{s0}{smallest scale of the wavelet. Default is \code{2*dt}}

\item{J1}{number of scales - 1.}

\item{max.scale}{maximum scale. Computed automatically if left unspecified.}

\item{mother}{type of mother wavelet function to use. Can be set to
\code{morlet}, \code{dog}, or \code{paul}. Default is \code{morlet}.}

\item{param}{nondimensional parameter specific to the wavelet function.}

\item{lag1}{AR(1) coefficient of time series used to test for significant
patterns.}

\item{sig.level}{significance level. Default is 0.95.}

\item{sig.test}{type of significance test. If set to 0, use a regular
\eqn{\chi^2} test. If set to 1, then perform a time-average test.
If set to 2, then do a scale-average test.}

\item{do.sig}{perform significance testing if \code{TRUE}. Default is
\code{TRUE}.}
}
\value{
Returns a \code{biwavelet} object containing:
\item{coi}{matrix containg cone of influence}
\item{wave}{matrix containing the wavelet transform}
\item{power}{matrix of power}
\item{power.corr}{matrix of bias-corrected power using the method described
                   by \code{Liu et al. (2007)}}
\item{phase}{matrix of phases}
\item{period}{vector of periods}
\item{scale}{vector of scales}
\item{dt}{length of a time step}
\item{t}{vector of times}
\item{xaxis}{vector of values used to plot xaxis}
\item{s0}{smallest scale of the wavelet }
\item{dj}{spacing between successive scales}
\item{sigma2}{variance of time series}
\item{mother}{mother wavelet used}
\item{type}{type of \code{biwavelet} object created (\code{wt})}
\item{signif}{matrix containg significance levels}
}
\description{
Compute wavelet transform
}
\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)

}
\author{
Tarik C. Gouhier (tarik.gouhier@gmail.com)

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.
\emph{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. \emph{Journal of Atmospheric and Oceanic
Technology} 24:2093-2102.
}