Interpretable, non-mechanistic forecasting using empirical dynamic modeling and interactive visualization.

ABSTRACT: Forecasting methods are notoriously difficult to interpret, particularly when the relationship between the data and the resulting forecasts is not obvious. Interpretability is an important property of a forecasting method because it allows the user to complement the forecasts with their own knowledge, a process which leads to more applicable results. In general, mechanistic methods are more interpretable than non-mechanistic methods, but they require explicit knowledge of the underlying dynamics. In this paper, we introduce EpiForecast, a tool which performs interpretable, non-mechanistic forecasts using interactive visualization and a simple, data-focused forecasting technique based on empirical dynamic modelling. EpiForecast's primary feature is a four-plot interactive dashboard which di

SUBMITTER: Mason L 

PROVIDER: S-EPMC10069763 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature