rLifting: High-Performance Wavelet Lifting Transforms

Performs Wavelet Lifting Transforms focusing on signal denoising and functional data analysis (FDA). Implements a hybrid architecture with a zero-allocation 'C++' core for high-performance processing. Features include unified offline (batch) denoising, causal (real-time) filtering using a ring buffer engine, and adaptive recursive thresholding.

Version:	0.9.0
Depends:	R (≥ 4.1.0)
Imports:	Rcpp
LinkingTo:	Rcpp
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, dplyr, ggplot2, microbenchmark
Published:	2026-02-20
DOI:	10.32614/CRAN.package.rLifting (may not be active yet)
Author:	Moises da Silva [aut, cre]
Maintainer:	Moises da Silva <moisesdff8 at gmail.com>
BugReports:	https://github.com/mkyou/rLifting/issues
License:	MIT + file LICENSE
URL:	https://github.com/mkyou/rLifting
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	rLifting results

Documentation:

Reference manual:	rLifting.html , rLifting.pdf
Vignettes:	3. Causal decomposition: the rLifting advantage (source, R code) 2. Benchmark: speed and reconstruction accuracy (source, R code) 5. Extensions and advanced usage (source, R code) 1. Introduction: offline, causal and online analysis (source, R code) 4. Real-time signal smoothing (source, R code)

Downloads:

Package source:	rLifting_0.9.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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