{"id":818,"date":"2015-06-26T19:24:48","date_gmt":"2015-06-26T19:24:48","guid":{"rendered":"http:\/\/kourentzes.com\/forecasting\/?p=818"},"modified":"2015-07-16T09:45:51","modified_gmt":"2015-07-16T09:45:51","slug":"isf-2015-and-invited-session-on-forecasting-with-combinations-and-hierarchies","status":"publish","type":"post","link":"https:\/\/kourentzes.com\/forecasting\/2015\/06\/26\/isf-2015-and-invited-session-on-forecasting-with-combinations-and-hierarchies\/","title":{"rendered":"ISF 2015 and invited session on \u201cForecasting with Combinations and Hierarchies\u201d"},"content":{"rendered":"

The International Symposium on Forecasting<\/a> (ISF 2015) was held this week in Riverside, CA. It was a very interesting conference, with stimulating talks and a wide variety of forecasting related topics, both for academics and practitioners. It is a highly recommended conference to attend.<\/p>\n

I organised the invited session on the topic of “Forecasting with Combinations and Hierarchies”. In my opinion these two are highly related topics, as hierarchical and grouped forecasting can be seen as a special case of forecast combinations. There were four talks in the this session, which you can find here:<\/p>\n

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  1. Wickramasuriya S.<\/strong>, Athanasopoulos G., Hyndman R. J., Forecasting Hierarchical Time Series Through Trace Minimization<\/a>.<\/li>\n
  2. Athanasopoulos G.<\/strong>, Hyndman R. J., Kourentzes N., Petropoulos F., Forecasting With Temporal Hierarchies<\/a>.<\/li>\n
  3. Barrow D.<\/strong>, Kourentzes N., To Combine Forecasts Or To Combine Forecast Models?<\/a><\/li>\n
  4. Athanasopoulos G., Hyndman R. J., Kourentzes N.<\/strong>, Petropoulos F., Using Temporal Hierarchies In Practice.<\/a><\/li>\n<\/ol>\n

    In boldface are the presenters. Presentations 2. and 4. are on the same topic, with George’s presentation discussing the theory behind temporal hierarchies and mine looking at case studies and implications for practice. Temporal hierarchies is the next step from the Multiple Aggregation Prediction Algorithm<\/a> (MAPA). In contrast to MAPA, temporal hierarchies are forecasting method independent and more powerful in terms of flexibility and combination options.<\/p>\n

    The session attracted interesting comments and discussions on the various presentations and I hope the audience enjoyed both the topics and the discussions.<\/p>\n

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