Computes the Forward WaveD Transform.

1 |

`y` |
Sample of |

`g` |
Sample of |

`L` |
Lowest resolution level; the default is 3. |

`deg` |
The degree of the Meyer wavelet, either 1, 2, or 3 (the default). |

`F` |
Finest resolution level; the default is the data-driven choice j1 (see Value below). |

`thr` |
A vector of length |

`SOFT` |
if SOFT=TRUE, uses the soft thresholding policy as opposed to the hard (SOFT=FALSE, the default). |

Returns a vector of wavelet coefficients of length n (the same length as y),
the last *n/2* entries are wavelet coefficients at resolution level *J-1*, where
*J= log_2(n)*; the *n/4* entries before that are the wavelet coefficients at
resolution level *J-2*, and so on until level L. In addition the *2^L* entries
are scaling coefficients at coarse level *C=L*.

Johnstone, I., Kerkyacharian, G., Picard, D. and Raimondo, M. (2004),
'Wavelet deconvolution in a periodic
setting', * Journal of the Royal Statistical Society, Series B* **
66**(3),547–573. with discussion pp.627–652.

Raimondo, M. and Stewart, M. (2006), ‘The WaveD Transform in R’, preprint, School and Mathematics and Statistics, University of Sydney.

1 2 3 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.