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

View source: R/retrieveBootstrapSample.R

Use the wavelet coefficients from the selected WiSE bootstrap model to construct smooth bootstrap series in the original time/space domain. This function may be of little use and creates large array objects within R. The wavelet coefficients are a preferable representation of the data, as they are sparse and contain the signal information.

1 | ```
retrieveBootstrapSample(WiSEObj)
``` |

`WiSEObj` |
an object obtained from |

The `wavethresh`

package is used to perform the inverse wavelet decomposition of each bootstrap sample of wavelet coefficients.

The bootstrap series will be smoothed to the selected threshold level, *J0=j* (see `WiSEBoot`

).

` BootSample ` |
an array. The rows contain each bootstrap sample – dimension is the |

Megan Heyman

For an overview of the wavelet methodology used in `wavethresh`

, see "Wavelet Methods for Statistics in R," (Nason, 2008).

1 2 3 4 5 6 7 | ```
someData <- rnorm(2^5)
##Bootstrap sample of size 10 is not recommended. For demonstration only.
bootInfo <- WiSEBoot(someData, R=10, J0=2)
bootSeries <- retrieveBootstrapSample(bootInfo)$BootSample
bootSeries[1, , 1] #this is the first bootstrap series
``` |

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