An Evaluation of Methods for Combining Univariate Time Series Forecasts
This thesis presents and evaluates nineteen methods for combining up to eleven automated univariate forecasts. The evaluation is made by applying the methods on a dataset containing more than 1000 monthly time series. The accuracy of one period ahead forecasts is analyzed. Almost 3.2 million forecasts are evaluated in the study. Methods that are using past forecasts to optimally produce a combined
