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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.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.threshold_method = "sure"): per-level Stein Unbiased Risk
Estimator, complementing the existing universal (VisuShrink) rule.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.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.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.denoise_signal_offline().denoise_signal_causal().new_wavelet_stream().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.