Method Comparison Matrix

This page is generated from MethodRegistry.list_catalog() and summarizes method-level behavior for onboarding, review, and machine-facing routing.

Current package version target: 0.1.1.

Method	Input mode	Backend	Maturity	Required/common params	Optional deps	Native	Multivariate	Output components	Recommended use
CEEMDAN	univariate	python	stable	trials (50), noise_width (0.05), primary_period (null)	PyEMD	no	univariate	trend, season, residual, components.imfs	noise-assisted EMD workflows; adaptive decomposition with improved IMF stability
EMD	univariate	python	stable	n_imfs (null), primary_period (null)	PyEMD	no	univariate	trend, season, residual, components.imfs	adaptive decomposition of nonlinear signals; IMF-oriented exploratory analysis
GABOR_CLUSTER	univariate	python	experimental	model (null), model_path (null)	faiss	no	univariate	trend, season, residual, components.clusters	research prototypes; exploratory clustering-style decomposition
MA_BASELINE	univariate	python	stable	trend_window (7), season_period (null)	none	no	univariate	trend, season, residual	sanity checks; lightweight baseline decomposition
MEMD	multivariate	optional-backend	optional-backend	primary_period (null)	PySDKit	no	shared-model	trend, season, residual, components.imfs	multivariate adaptive decomposition; shared oscillatory modes across channels
MSSA	multivariate	python	flagship	window (required), rank (null), primary_period (null)	none	no	shared-model	trend, season, residual, components.elementary	multivariate component recovery; shared seasonal structure across channels
MSTL	univariate	wrapper	stable	periods (required)	statsmodels	no	univariate	trend, season, residual, components.seasonal_terms	multiple seasonalities in univariate data; classical decomposition baselines
MVMD	multivariate	optional-backend	optional-backend	K (4), alpha (2000.0), primary_period (null)	PySDKit	no	shared-model	trend, season, residual, components.modes	multivariate variational decomposition; shared frequency structure across channels
ROBUST_STL	univariate	wrapper	stable	period (required)	statsmodels	no	univariate	trend, season, residual	outlier-prone seasonal-trend baselines; classical robust decomposition
SSA	univariate	native-backed	flagship	window (required), rank (null), primary_period (null)	none	yes	univariate	trend, season, residual, components.elementary	accuracy-first univariate decomposition; component recovery
STD	channelwise	native-backed	flagship	period (required)	none	yes	channelwise	trend, season, residual, components.dispersion, components.seasonal_shape	fast seasonal-trend baselines; channelwise multivariate workflows
STDR	channelwise	native-backed	flagship	period (required)	none	yes	channelwise	trend, season, residual, components.dispersion, components.seasonal_shape	robust seasonal-trend decomposition; channelwise multivariate workflows
STL	univariate	wrapper	stable	period (required)	statsmodels	no	univariate	trend, season, residual	classical seasonal-trend baselines; statsmodels-compatible workflows
VMD	univariate	python	stable	K (4), alpha (2000.0), primary_period (null)	vmdpy, sktime	no	univariate	trend, season, residual, components.modes	band-limited mode separation; frequency-structured univariate workflows
WAVELET	univariate	wrapper	stable	wavelet ("db4"), level (null)	PyWavelets	no	univariate	trend, season, residual, components.coefficients	multiscale exploratory analysis; wavelet-style trend and detail separation

Use Config Reference for full DecompositionConfig field semantics and per-method parameter descriptions.

Use Method References for primary literature and official upstream package links.