complete-api-reference

name	complete-api-reference
description	Provides complete constructor and method signatures for all skforecast forecasters, backtesting functions, search functions, cross-validation classes, preprocessing, feature selection, and drift detection. Use when the user needs exact parameter names, types, or defaults for any skforecast class or function.

Complete API Reference

When to Use

Use this when you need exact parameter names, types, defaults, or method signatures for any skforecast class or function.

Related skills

• Prerequisite: choosing-a-forecaster (pick the class first; this skill only supplies its signature)
• Alongside: any workflow skill (they show the idiomatic usage, this one the exact arguments)
• Next: troubleshooting-common-errors (when a signature looks right but the call still fails)

Quick Index

Forecaster Constructors

• ForecasterRecursive — single series, recursive strategy
• ForecasterRecursiveMultiSeries — multiple series, global model
• ForecasterDirect — single series, one model per step
• ForecasterDirectMultiVariate — multiple input series, one target
• ForecasterRecursiveClassifier — classification-based
• ForecasterStats — statistical models (ARIMA, ETS, SARIMAX, ARAR)
• ForecasterEquivalentDate — baseline using past offsets
• ForecasterRnn — deep learning (RNN/LSTM/GRU)
• ForecasterFoundation — zero-shot with foundation models (Chronos-2, TimesFM 2.5, Moirai-2, TabICL, TabPFN-TS, TFC-T0, Nori, TS-IC)
• FoundationModel — low-level foundation model wrapper used by ForecasterFoundation

Forecaster Methods

• fit() — train the model
• predict() — generate point forecasts
• predict_interval() — generate prediction intervals

Model Selection

• backtesting_forecaster — backtest single-series forecasters
• backtesting_forecaster_multiseries — backtest multi-series forecasters
• backtesting_stats — backtest statistical models
• backtesting_foundation — backtest ForecasterFoundation (zero-shot)
• grid_search_forecaster / grid_search_forecaster_multiseries / grid_search_stats
• random_search_forecaster / random_search_forecaster_multiseries / random_search_stats
• bayesian_search_forecaster / bayesian_search_forecaster_multiseries
• bayesian_search_foundation — tune ForecasterFoundation inference-time parameters
• grid_search_equivalent_date — tune ForecasterEquivalentDate baselines
• TimeSeriesFold — multi-step cross-validation
• OneStepAheadFold — fast one-step cross-validation

Feature Selection

• select_features — single series
• select_features_multiseries — multi-series

Drift Detection

• RangeDriftDetector — lightweight range check
• PopulationDriftDetector — statistical tests

Preprocessing

• RollingFeatures — rolling window statistics
• TimeSeriesDifferentiator — differencing
• CalendarFeatures — calendar features

References

Full constructor and method signatures for all public skforecast classes and functions, split by domain:

• Forecaster constructors: See references/forecaster-constructors.md
• Forecaster methods (fit(), predict(), predict_interval(), predict_quantiles(), predict_dist(), set_params(), set_lags(), set_out_sample_residuals(), availability matrix): See references/forecaster-methods.md
• Backtesting, search, cross-validation, feature selection: See references/model-selection-signatures.md
• Drift detection and preprocessing: See references/preprocessing-signatures.md