| 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() signatures
set_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 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)
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
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
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
DateTimeFeatureTransformer — calendar features