R: Testing the Wavelet Packet Tree for White Noise

wpt.test {waveslim} | R Documentation

## Testing the Wavelet Packet Tree for White Noise

### Description

A wavelet packet tree, from the discrete wavelet packet transform (DWPT), is tested node-by-node for white noise. This is the first step in selecting an orthonormal basis for the DWPT.

### Usage

    cpgram.test(y, p = 0.05, taper = 0.1)
    css.test(y)
    entropy.test(y)
    portmanteau.test(y, p = 0.05, type = "Box-Pierce")

### Arguments

`y` | wavelet packet tree (from the DWPT)
`p` | significance level
`taper` | weight of cosine bell taper (`cpgram.test` only)
`type` | `"Box-Pierce"` and `other` recognized (`portmanteau.test` only)

### Details

Top-down recursive testing of the wavelet packet tree is

### Value

Boolean vector of the same length as the number of nodes in the wavelet packet tree.

### Author(s)

B. Whitcher

### References

Brockwell and Davis (1991) Time Series: Theory and Methods, (2nd. edition), Springer-Verlag.

Brown, Durbin and Evans (1975) Techniques for testing the constancy of regression relationships over time, Journal of the Royal Statistical Society B, 37, 149-163.

Percival, D. B., and A. T. Walden (1993) Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques, Cambridge University Press.

### See Also

`ortho.basis`.

### Examples

    data(mexm)
    J <- 6
    wf <- "la8"
    mexm.dwpt <- dwpt(mexm[-(1:4)], wf, J)
    ## Not implemented yet
    ## plot.dwpt(x.dwpt, J)
    mexm.dwpt.bw <- dwpt.brick.wall(mexm.dwpt, wf, 6, method="dwpt")
    mexm.tree <- ortho.basis(portmanteau.test(mexm.dwpt.bw, p=0.025))
    ## Not implemented yet
    ## plot.basis(mexm.tree)

[Package waveslim version 1.7.5 Index]