| name | complete-api-reference |
| description | Complete constructor signatures 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 This Skill
Use this when you need exact parameter names, types, defaults, or method signatures for any skforecast class or function.
Overview
This skill contains the full constructor and method signatures for all
public skforecast classes and functions. See
references/method-signatures.md for
the complete reference, including:
- All forecaster constructors
fit(), predict(), predict_interval(), predict_quantiles(), predict_dist() signaturesset_params(), set_lags(), set_out_sample_residuals() signatures- Method availability matrix (which forecaster supports which method)
- Backtesting, search, cross-validation, feature selection, and drift detection signatures
Quick Index
Forecaster Constructors
ForecasterRecursive — single series, recursive strategyForecasterRecursiveMultiSeries — multiple series, global modelForecasterDirect — single series, one model per stepForecasterDirectMultiVariate — multiple input series, one targetForecasterRecursiveClassifier — classification-basedForecasterStats — statistical models (ARIMA, ETS, SARIMAX, ARAR)ForecasterEquivalentDate — baseline using past offsetsForecasterRnn — deep learning (RNN/LSTM/GRU)ForecasterFoundation — zero-shot with foundation models (Chronos-2, TimesFM 2.5, Moirai-2, TabICL, TabPFN-TS, TFC-T0)FoundationModel — low-level foundation model wrapper used by ForecasterFoundation
Forecaster Methods
fit() — train the modelpredict() — generate point forecastspredict_interval() — generate prediction intervals
Model Selection
backtesting_forecaster — backtest single-series forecastersbacktesting_forecaster_multiseries — backtest multi-series forecastersbacktesting_stats — backtest statistical modelsgrid_search_forecaster / grid_search_forecaster_multiseries / grid_search_statsrandom_search_forecaster / random_search_forecaster_multiseries / random_search_statsbayesian_search_forecaster / bayesian_search_forecaster_multiseriesTimeSeriesFold — multi-step cross-validationOneStepAheadFold — fast one-step cross-validation
Feature Selection
select_features — single seriesselect_features_multiseries — multi-series
Drift Detection
RangeDriftDetector — lightweight range checkPopulationDriftDetector — statistical tests
Preprocessing
RollingFeatures — rolling window statisticsTimeSeriesDifferentiator — differencingCalendarFeatures — calendar features
