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Model library

Multivariate, penalized models

Penalized forecasting models add a penalty to large or complex parameters to reduce overfitting, improve generalization, and handle many predictors.

Ridge Regression

This is a way of using Bayesian models in a VAR framework. Prior to Lasso, the most widely used method for choosing which variables to include was stepwise…

Read moreVARX Elastic Net

The elastic net is a regression method that linearly combines the lasso and ridge (see below) methods. Basically, the elastic net method finds the ridge…

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Vector Error Correction Models are useful for data sets with long-run relationships (also called cointegration). VECMs are useful for estimating both…

Read moreVARX Lasso

Lasso, Least Absolute Shrinkage and Selection Operator is the most successful application of AI within econometrics. Lasso was introduced in order to improve…

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MethodThe methodology

Cross-temporal hierarchies, reconciliation weights and the research behind them.

Read moreModelsThe model library

80+ univariate, econometric, penalized and machine-learning models.

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Click through variable selection, models and scenarios yourself.

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