R: Discrete Wavelet transform features.

extractFDAWavelets {mlr} | R Documentation

## Discrete Wavelet transform features.

### Description

The function extracts discrete wavelet transform coefficients from the raw functional data. See wavelets::dwt for more information.

### Usage

    extractFDAWavelets(filter = "la8", boundary = "periodic")

### Arguments

`filter` | (`character(1)`) Specifies which filter should be used. Must be one of `d`|`la`|`bl`|`c` followed by an even number for the level of the filter. The level of the filter needs to be smaller or equal then the time-series length. For more information and acceptable filters see `help(wt.filter)`. Defaults to `la8`.
`boundary` | (`character(1)`) Boundary to be used. “periodic” assumes circular time series, for “reflection” the series is extended to twice its length. Default is “periodic”.

### Value

(data.frame).

### See Also

Other fda_featextractor: `extractFDABsignal()`, `extractFDADTWKernel()`, `extractFDAFPCA()`, `extractFDAFourier()`, `extractFDAMultiResFeatures()`, `extractFDATsfeatures()`

[Package mlr version 2.19.0 Index]