wavDictionary: Constructor function for objects of class wavDictionary
In wmtsa: Wavelet Methods for Time Series Analysis

Description Usage Arguments Details Value S3 METHODS See Also Examples

Packs input information regarding a discrete wavelet transform into a dictionary list.

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wavDictionary(wavelet, dual, decimate, n.sample,
    attr.x, n.levels, boundary, conv, filters,
    fast, is.complex)

`wavelet`	a character string denoting the type of wavelet used in the transform.
`dual`	a logical value. If `TRUE`, it signifies that a dual transform was performed.
`decimate`	a logical value. If `TRUE`, it signifies that a decimated transform was performed.
`n.sample`	an integer representing the number of samples in the original time series.
`attr.x`	a list of additional (arbitrary) attributes to append onto the output object.
`n.levels`	an integer denoting the number of decomposition levels.
`boundary`	a character string denoting the boundary extension type used in transform. Supported values are `"zero"`, `"periodic"`, `"reflection"`, and `"continue"`.
`conv`	a logical value. If `TRUE`, it signifies that a convolution style transform was performed (as opposed to correlation style).
`filters`	a list of vectors named `"scaling"` and `"wavelet"` containing the scaling and wavelet filter coefficients, respectively.
`fast`	a logical value. If `TRUE`, it signifies that a fast pyramidal scheme was used to develop the decimated transform as opposed to calculating the transform coefficients via an explicit matrix multiplication of the wavelet transform matrix and the original time series.
`is.complex`	a logical value. If `TRUE`, it signifies the transform was complex-valued.

Used internally by the wavMODWT and wavDWT functions to package the transform contents into a dictionary list.

an object of class wavDictionary.

print

print the dictionary.

Usage: print(x)

wavDWT, wavMODWT.

## create a faux wavelet dictionary 
wavelet <- "s8"
wavDictionary(wavelet=wavelet, dual=FALSE,
    decimate=FALSE, n.sample=1024,
    attr.x=NULL, n.levels=3,
    boundary="periodic", conv=TRUE,
    filters=wavDaubechies(wavelet),
    fast=TRUE, is.complex=FALSE)