For a given wavelet computes a list with each entry of the list containing that discrete wavelet at a different scale. The first entry corresponds to the finest wavelet, the next entry to the next finest, and so on.

1 |

`J` |
A NEGATIVE integer. -J is the maximum number of levels to compute. |

`filter.number` |
The filter number (number of vanishing moments) of the underlying wavelet to use. |

`family` |
The family of the wavelet. See |

A list of length J. The first entry contains the discrete wavelet at the finest scale, the 2nd entry contains the next most finest wavelet, and so on.

Guy Nason.

Nason, G.P. (2013) A test for second-order stationarity and
approximate confidence intervals for localized autocovariances
for locally stationary time series. *J. R. Statist. Soc.* B,
**75**, 879-904.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
#
# E.g. compute discrete Haar wavelets on scales 1, 2, 3.
#
mkcoef(-3, 1, "DaubExPhase")
#[[1]]
#[1] 0.7071068 -0.7071068
#
#[[2]]
#[1] 0.5 0.5 -0.5 -0.5
#
#[[3]]
#[1] 0.3535534 0.3535534 0.3535534 0.3535534 -0.3535534 -0.3535534 -0.3535534
#[8] -0.3535534
``` |

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