- Version 0.4.0
- Sold by i4cast LLC
Long-Memory Dynamic Factor Model (LMDFM) to analyze and forecast large number of time-series influenced by evolutions of unobserved factors.
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Long-Memory Dynamic Factor Model (LMDFM) to analyze and forecast large number of time-series influenced by evolutions of unobserved factors.
Variational Bayesian filtering Factor Analysis (VBfFA) to estimate time-varying statistical factors of large set of multiple time-series
Long-Memory Vector Autoregression (LMVAR) to analyze and forecast multiple time-series influenced by common factors and hidden components.
Dynamic Factor Variance-Covariance Model (DFVCM) makes multi-step forecasts of large variance-covariance matrix with dynamic factor model.
Yule-Walker-PCA Autoregressive Model (YWpcAR) to analyze and forecast many time-series individually with evolution of hidden components.
Continuously Trained Vector Autoregressive Forecast (CTVARF) for multiple time-series influenced by common factors and hidden components.
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