Recently I posted about a paper I co-authored with Fotios Petropoulos, now in JORS: Forecast Combinations for Intermittent Demand. There we found that for intermittent demand data using multiple levels of temporal aggregation, forecasting them with the appropriate models and finally combining the forecasts performed best. This approach has many analogies with the MAPA algorithm… Read More »
A new package for analysing and forecasting intermittent demand time series and slow moving items has been release for R. You can download the latest version from CRAN. The launch version contains the following functions: crost: Croston’s method and variants. crost.ma: Moving average with Croston’s method decomposition. idclass: Time series categorisation for intermittent demand. simID:… Read More »
N. Kourentzes, 2014, International Journal of Production Economics, 156: 180-190. http://dx.doi.org/10.1016/j.ijpe.2014.06.007
N. Kourentzes, 2012, The 32nd Annual international Symposium on Forecasting, Boston.