R: Data analytic wavelet thresholding routine

TOthreshda2 {wavethresh} | R Documentation

## Data analytic wavelet thresholding routine

### Description

This function might be better called using the regular `threshold` function using the `op2` policy.

Corresponds to the wavelet thresholding routine developed by Ogden and Parzen (1994) Data dependent wavelet thresholding in nonparametric regression with change-point applications. Tech Rep 176, University of South Carolina, Department of Statistics.

### Usage

    TOthreshda2(ywd, alpha = 0.05, verbose = FALSE, return.threshold = FALSE)

### Arguments

`ywd` | The `wd.object` that you wish to threshold.
`alpha` | The smoothing parameter which is a p-value
`verbose` | Whether messages get printed
`return.threshold` | If TRUE then the threshold value gets returned rather than the actual thresholded object

### Details

The TOthreshda2 method operates in a similar fashion to `TOthreshda1` except that it takes the cumulative sum of squared coefficients, creating a sample "Brownian bridge" process, and then using the standard Kolmogorov-Smirnov statistic in testing.

In this situation, the level of the hypothesis tests, alpha, has default value 0.05. Note that the choice of alpha controls the smoothness of the resulting wavelet estimator – in general, a relatively large alpha makes it easier to include coefficients, resulting in a more wiggly estimate; a smaller alpha will make it more difficult to include coefficients, yielding smoother estimates.

### Value

Returns the threshold value if `return.threshold==TRUE` otherwise returns the shrunk set of wavelet coefficients.

### Author(s)

Todd Ogden

### See Also

`threshold`,`TOthreshda1`, `wd`

[Package wavethresh version 4.6.8 Index]