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complete-api-reference

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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.

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Source SKILL.md: https://github.com/skforecast/skforecast/blob/HEAD/skills/complete-api-reference/SKILL.md

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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, TabPFN-TS, TFC-T0)
  • 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
  • CalendarFeatures — calendar features