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Model library

Multivariate, mixed frequency models

Mixed frequency forecasting models use higher frequency data to predict outcomes at a lower frequency and are commonly applied in nowcasting.

MIDAS

Mixed Data Sampling (MIDAS) models use high frequency indicators to predict a low frequency variable. By fitting a lag distribution function the number of…

Read moreMIDAS Lasso

Mixed Data Sampling (MIDAS) models use high frequency indicators to predict a low frequency variable. By applying a lasso penalty function the parameters are…

Read moreMIDAS Sparse Group Penalty

Mixed Data Sampling (MIDAS) models use high frequency indicators to predict a low frequency variable. By applying a sparse group penalty function the…

Read moreUnrestricted MIDAS

Unrestricted Mixed Data Sampling (MIDAS) models use high frequency indicators to predict a low frequency…

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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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