Abbreviation: WaveletValDaub12
Category: Wavelet
Input Parameters:
| Name | Range | Default |
| Time Series | Close | |
| Window Exponent | 1 <= Int <= 10 | 6 |
| Wavelet Number | 1 <= Int <= 2^WinExponent | 1 |
Calculation:
Daubechies12Wavelet(X,n)(W)
Calculates discrete Daubechies-12 wavelet transform of X over the last n points. Returns value of Wth wavelet coefficient. W=1 returns the value of Smoothing (bias) coefficient,
where
X = Time Series
n = 2^Window Exponent
W = Wavelet Number
Discussion:
Wavelet transform performs decomposition of the time series into a row of wavelets, each with its own coefficient. Wavelets of different hierarchy levels (wavelets with numbers 1; 2; 3..4; 5..8; 9..16; …; 2^(k-1)+1..2^k) describe different scale details in the decomposed time series, with level of detail increasing from level to level. For more information on Wavelets refer to Wavelet Discussion.
For more details, refer to Wavelets and Filter Banks, by Gilbert Strang and Truong Nguyen (Wellesley ‘ Cambridge Press, 1996).