Advanced Forecasting with Python by Joos Korstanje

Author:Joos Korstanje
Language: eng
Format: epub
ISBN: 9781484271506
Publisher: Apress

Key Takeaways

The VAR model uses multivariate correlation to make one model for multiple target variables.

The order of the VAR model, p, determines the number of time steps back that are used for predicting the future.

The VAR model implementation can define the ideal number of lags using the maxlags parameter and the Akaike Information Criterion.

The VAR model needs to estimate a large number of parameters, which makes it require a huge amount of historical data. This makes it difficult to estimate higher lags.

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