Description Usage Arguments Value Author(s) References See Also Examples

View source: R/hardThresholding.R

This function projects *n* indepedent processes on a common wavelet basis and shrinks to zero the *n* coefficients whose *\ell_2*-norm is lower than a threshold.

1 | ```
hardThresholding(xdata, delta, verbose = FALSE, varName = NULL, wavFilter="s8")
``` |

`xdata` |
The matrix of |

`delta` |
The desired threshold. If missing, an automatic threshold is computed. |

`verbose` |
Should the details be printed. |

`varName` |
The name of the current functional variable. |

`wavFilter` |
A character string denoting the filter type. Supported types include: EXTREMAL PHASE (daublet): ‘haar’, ‘d2’, ‘d4’, ‘d6’, ‘d8’, ‘d10’, ‘d12’, ‘d14’, ‘d16’, ‘d18’, ‘d20’ LEAST ASYMMETRIC (symmlet): ‘s2’, ‘s4’, ‘s6’, ‘s8’, ‘s10’, ‘s12’, ‘s14’, ‘s16’, ‘s18’, ‘s20’ BEST LOCALIZED: ‘l2’, ‘l4’, ‘l6’, ‘l14’, ‘l18’, ‘l20’ COIFLET: ‘c6’, ‘c12’, ‘c18’, ‘c24’, ‘c30’ Default: ‘s8’. |

A list with two components

`mht.names` |
The names of the common wavelet basis after thresholding the coefficients. |

`estimatedDesign` |
The new design matrix after thresholding. |

Baptiste Gregorutti

Gregorutti, B., Michel, B. and Saint Pierre, P. (2015). Grouped variable importance with random forests and application to multiple functional data analysis, Computational Statistics and Data Analysis 90, 15-35.

1 2 3 |

```
Loading required package: randomForest
randomForest 4.6-14
Type rfNews() to see new features/changes/bug fixes.
Loading required package: wmtsa
Loading required package: fda
Loading required package: splines
Loading required package: Matrix
Attaching package: 'fda'
The following object is masked from 'package:graphics':
matplot
Automatic threshold 0.0485696
59 selected coefficients using multiple hard-thresholding. Filter: s8
```

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