@conference {Sarhani201479, title = {An extension of X13-ARIMA-SEATS to forecast islamic holidays effect on logistic activities}, booktitle = {Proceedings of 2nd IEEE International Conference on Logistics Operations Management, GOL 2014}, year = {2014}, note = {cited By 0}, pages = {79-84}, abstract = {To better manage and optimize logistic activities, factors that affect it must be determined: The calendar effect is one of these factors which must be analyzed. Analyzing such kind of data by using classical time series forecasting methods, such as exponential smoothing method and ARIMA model, will fail to capture such variation. This paper is released to present a review of the models which are used to forecast the calendar effect, especially moving holidays effect. We adopt the recent approach of X13-ARIMA-SEATS and extend it for being able to forecast the effect of Islamic holidays. Our extension is applied to Moroccan case studies, and aims to give recommendations concerning this effect on logistic activities. {\textcopyright} 2014 IEEE.}, doi = {10.1109/GOL.2014.6887423}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908655728\&doi=10.1109\%2fGOL.2014.6887423\&partnerID=40\&md5=de88391f3f7ec0517e753c7aeb4aeae4}, author = {Sarhani, M. and El Afia, A.} }