WaveFEX: Wavelet-based Feature EXtraction
In fabnavarro/rwavelet: Wavelet Analysis

WaveFEX

R Documentation

Wavelet-based Feature EXtraction

Description

Todo: add description

Usage

WaveFEX(type = "PO", obs, qmf, scale = log2(nrow(obs)), iwt = F, alpha = F)

Arguments

`type`	Orthogonal transform: PO or translation invariant transform:TI.
`obs`	A matrix of n x p functional data (n should be a power of 2).
`qmf`	Orthonormal quadrature mirror filter.
`scale`	Finest scale of the decomposition.
`iwt`	Logical to specify forward (FALSE) or inverse (TRUE) wavelet transform.
`alpha`	Logical TRUE to include scaling coefficients at the first scale.

Value

contj Matrix scale x p of Squared norm of the wavelet coefficient at each scale.

wc wavelet coefficients matrix.

References

Antoniadis, A., Brossat, X., Cugliari, J., & Poggi, J. M. (2013). Clustering functional data using wavelets. Int. J. Wavelets Multiresolution Inf. Process., 11(01), 1350003.

Cheam, A., Fredette, M., Marbac, M., & Navarro, F. (2023). Translation-invariant functional clustering on COVID-19 deaths adjusted on population risk factors. J. R. Stat. Soc., C: Appl. Stat., 72(2), 387-413.

fabnavarro/rwavelet documentation built on Nov. 5, 2023, 1:01 p.m.