The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

rLifting 1.0.0

New features

• Native irregular-grid support: pass a sorted t vector to denoise_signal_offline(), denoise_signal_causal(), or t_val per sample to the stream closure from new_wavelet_stream(). The predict step uses Lagrange interpolation conditioned on the actual sample positions — no separate regularisation required.
• Two new boundary extensions: local_linear (OLS extrapolation with configurable neighbourhood ll_k) and one_sided (renormalised filter at the edge), bringing the total to five alongside the existing symmetric, periodic, and zero.
• SureShrink threshold rule (threshold_method = "sure"): per-level Stein Unbiased Risk Estimator, complementing the existing universal (VisuShrink) rule.
• SCAD shrinkage (shrinkage = "scad"): Smoothly Clipped Absolute Deviation (Antoniadis & Fan, 2001), added alongside the existing hard, soft, and semisoft shrinkages.
• tune_alpha_beta(): automatic selection of the recursive threshold parameters α and β by minimising SURE over the signal.
• diagnose_wavelet(): verification suite for custom wavelets — perfect reconstruction, vanishing moments, orthogonality, compact support, and shift sensitivity.
• Seven benchmark datasets bundled: benchmark_rlifting, benchmark_wavethresh, benchmark_adlift, benchmark_nlt, benchmark_rlifting_irregular, benchmark_adlift_irregular, benchmark_nlt_irregular — each based on 1,000 Monte Carlo replications per configuration.
• Eight vignettes: introduction, thresholding and tuning, causal/stream, boundary modes, irregular grids, extensions, full cross-package benchmarks, and a real-world case study (BabyECG infant cardiac monitoring).

Deprecated

• The method argument in denoise_signal_offline() and denoise_signal_causal() is deprecated in favour of the separate threshold_method and shrinkage arguments. Old code continues to work via a backward-compatibility shim; method will be removed in a future version.

rLifting 0.9.0

• Initial release of the package.
• Implements high-performance Wavelet Lifting Transforms.
• Features:
  • Unified offline (batch) denoising via denoise_signal_offline().
  • Causal (sliding-window) filtering via denoise_signal_causal().
  • Sample-by-sample stream processing via new_wavelet_stream().
  • Adaptive recursive thresholding (universal rule, hard/soft/semisoft shrinkage).
  • Zero-allocation ‘C++’ core via ‘Rcpp’.
  • Six built-in wavelets: Haar, DB2, CDF 5/3, CDF 9/7, DD4, Lazy.
  • Three boundary extensions: symmetric, periodic, zero.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.