Utilities for Scoring and Assessing Predictions
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Updated
May 24, 2024 - R
Utilities for Scoring and Assessing Predictions
Easily evaluate your forecasts with (multivariate) Diebold-Mariano and (multivariate) Giacomini-White tests of equal predictive ability and MCS.
Comparing sequential forecasters via confidence sequences & e-processes
Forecast Evaluation Package for gretl
Analysis on the quality and determinants of economic forecasts during the Covid 19 pandemic
Analysis on the quality and determinants of economic forecasts pre-Covid 19
Multi Horizon Superior Predictive Ability (SPA) test proposed by Quaedvlieg (2021)
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
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.
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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