EBMAforecast

Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in this package are Montgomery, Hollenbach, and Ward (2015) doi:10.1016/j.ijforecast.2014.08.001 and Montgomery, Hollenbach, and Ward (2012) doi:10.1093/pan/mps002.

Last 30 days

This package has been downloaded 539 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 26 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 8,517 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Apr 17, 2024 with 62 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.