Elucidate structure in intermittent demand time series
Nikolaos Kourentzes and George Athanasopoulos, 2020. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2020.05.046
Nikolaos Kourentzes and George Athanasopoulos, 2020. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2020.05.046
N. Kourentzes, D. Li and A.K. Strauss, 2017. Journal of Revenue & Pricing Management.
F. Petropoulos, N. Kourentzes and K. Nikolopoulos, 2016, International Journal of Production Economics, 181: 154-161. http://dx.doi.org/10.1016/j.ijpe.2016.04.017
Together with Fotios Petropoulos we gave a workshop on producing forecasts with R, at the International Symposium on Forecasting, 2016. You can find the material of the workshop here. The workshop notes assume knowledge of what the various forecasting methods do, which are only briefly explained in the workshop’s slides, and mostly focuses in showing… Read More »
Although Croston’s method and its variants are popular for intermittent demand time series, there have been limited advances in identifying how to select appropriate smoothing parameters and initial values. From the one hand this complicates forecasting for organisations, and from the other hand it does not permit automation. Recent research investigated various cost functions for… 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