Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.
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Updated
Dec 11, 2018 - Jupyter Notebook
Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.
Utilities for Scoring and Assessing Predictions
Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
Comparing sequential forecasters via confidence sequences & e-processes
Easily evaluate your forecasts with (multivariate) Diebold-Mariano and (multivariate) Giacomini-White tests of equal predictive ability and MCS.
Multi Horizon Superior Predictive Ability (SPA) test proposed by Quaedvlieg (2021)
This code mainly computes the forecast of headline inflation using different aproaches. Likewise presents the forecast evaluation for each model along different points in a span period.
Analysis on the quality and determinants of economic forecasts during the Covid 19 pandemic
Supplementary materials for the following publication: Davydenko, A., & Goodwin, P. (2021). Assessing point forecast bias across multiple time series: Measures and visual tools. International Journal of Statistics and Probability, 10(5), 46-69. https://doi.org/10.5539/ijsp.v10n5p46
self archived publications
Analysis on the quality and determinants of economic forecasts pre-Covid 19
Forecast Evaluation Package for gretl
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