# FWaveD

### Description

Computes the Forward WaveD Transform.

### Usage

1 |

### Arguments

`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). |

### Value

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*.

### References

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.

### See Also

`WaveD`

### Examples

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