Flow Field Forecasting for Univariate Time Series

摘要

A statistical learning methodology, called flow field forecasting, is presented for predicting the future of a univariate time series. Flow field forecasting draws information from an interpolated flow field of the observed time series to incrementally build a forecast. The time series need not have uniformly spaced observations. Included in the presentation are measures of assessment, a procedure for forecast updating as new data arrive and a performance comparison of flow field forecasting with other major forecasting techniques.