sqrt.est

sqrt.est

sqrt.est(noisy, wav.filter.number = 4, family = "DaubLeAsymm", theta = 0.01, ti = T)

Performs the SQRT denoising algorithm as described in the paper. Requires WaveThresh.

Takes:

noisy The noisy vector; its length has to be a power of two.

wav.filter.number The wavelet filter number of the wavelet basis used for denosing. Can be between 1 and 10 if family = "DaubExPhase", and between 4 and 10 if family = "DaubLeAsymm".

family The wavelet family name of the wavelet basis used for denosing. Can be set to "DaubExPhase" (Daubechies' Extremal Phase) or "DaubLeAsymm" (Daubechies' Least Asymmetric).

theta The theta parameter of the thresholding profile; must be between 0 and 1.

ti If T, then the translation-invariant version of the algorithm is performed. If F, then the algorithm is based on the traditional Discrete Wavelet Transform.

Returns:

denv The denoised vector.

noisy	The noisy vector; its length has to be a power of two.
wav.filter.number	The wavelet filter number of the wavelet basis used for denosing. Can be between 1 and 10 if family = "DaubExPhase", and between 4 and 10 if family = "DaubLeAsymm".
family	The wavelet family name of the wavelet basis used for denosing. Can be set to "DaubExPhase" (Daubechies' Extremal Phase) or "DaubLeAsymm" (Daubechies' Least Asymmetric).
theta	The theta parameter of the thresholding profile; must be between 0 and 1.
ti	If T, then the translation-invariant version of the algorithm is performed. If F, then the algorithm is based on the traditional Discrete Wavelet Transform.