Prequential methods

timecave.validation_methods.prequential

This module contains all the Prequential ('Predictive Sequential') validation methods supported by this package. These methods are also known as Forward Validation methods.

Classes:

Name	Description
GrowingWindow	Implements every variant of the Growing Window method.
RollingWindow	Implements every variant of the Rolling Window method.

See also

Out-of-Sample methods: Out-of-sample methods for time series data.

Cross-validation methods: Cross-validation methods for time series data.

Markov methods: Markov cross-validation method for time series data.

Notes

Predictive Sequential, or "Prequential", methods are one of the three main classes of validation methods for time series data (the others being out-of-sample methods and cross-validation methods). Unlike cross-validation methods, this class of methods preserves the temporal order of observations, although it differs from out-of-sample methods in that it partitions the series into equally sized folds. For more details on this class of methods, the reader should refer to [1].

References

1

Vitor Cerqueira, Luis Torgo, and Igor Mozetiˇc. Evaluating time series forecasting models: An empirical study on performance estimation methods. Machine Learning, 109(11):1997–2028, 2020.