Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

Solar forecasters have hitherto been restricting the application of numerical weather
prediction (NWP) to day-ahead forecasting scenarios. With the hourly updated NWP models …

Demand forecasting is a scientific and methodical assessment of future demand for a critical
product. The effective Demand Forecast Model (DFM) enables pharmaceutical companies to …

Forecast combinations were big winners in the M4 competition. This note reflects on and
analyzes the reasons for the success of forecast combination. We illustrate graphically how …

In the era of modern technology, the competitive paradigm among organisations is changing
at an unprecedented rate. New success measures are applied to the organisation's supply …

Feature-based time series representations have attracted substantial attention in a wide
range of time series analysis methods. Recently, the use of time series features for forecast …

Forecasting plays an indispensable role in grid integration of solar energy, which is an
important pathway toward the grand goal of achieving planetary carbon neutrality. This …

Several procedures to forecast daily risk measures in cryptocurrency markets have been
recently implemented in the literature. Among them, long‐memory processes, procedures …

Forecast combinations have been widely applied in the last few decades to improve
forecasting. Estimating optimal weights that can outperform simple averages is not always …

In this paper, we present an algorithm designed to automatically merge predictions from a
collection of individual prediction methods coded in R. The algorithm employs varying …