wavelets (version 0.2-6)

mra: Multiresolution Analysis

Description

Computes the multiresolution analysis for a univariate or multivariate time series.

Usage

mra(X, filter="la8", n.levels, boundary="periodic", fast=TRUE, method="dwt")

Value

• Returns an object of class mra, which is an S4 object with slots
• D
  A list with element $i$ comprised of a matrix containing the $i$th level wavelet detail.
• S
  A list with element $i$ comprised of a matrix containing the $i$th level wavelet smooths.
• filter
  A wt.filter object containing information for the filter used in the decomposition. See help(wt.filter) for details.
• level
  An integer value representing the level of wavelet decomposition.
• boundary
  A character string indicating the boundary method used in the wavelet decomposition. Valid values are "periodic" or "reflection".
• series
  The original time series, X, in matrix format.
• class.X
  A character string indicating the class of the input series. Possible values are "ts", "mts", "numeric", "matrix", or "data.frame".
• attr.X
  A list containing the attributes information of the original time series, X. This is useful if X is an object of class ts or mts and it is desired to retain relevant time information. If the original time series, X, is a matrix or has no attributes, then attr.X is an empty list.
• method
  A character string indicating which type of wavelet decomposition was performed (either "dwt" or "modwt").

References

Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.

See Also

dwt, modwt, wt.filter.

Examples

# obtain the two series listed in Percival and Walden (2000), page 42
X1 <- c(.2,-.4,-.6,-.5,-.8,-.4,-.9,0,-.2,.1,-.1,.1,.7,.9,0,.3)
X2 <- c(.2,-.4,-.6,-.5,-.8,-.4,-.9,0,-.2,.1,-.1,.1,-.7,.9,0,.3)

# combine them and compute MRA
newX <- cbind(X1,X2)
mra.out <- mra(newX, n.levels=3, boundary="reflection")