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Quantile Forecasting in Operational Planning and Inventory Management – an Initial Empirical Verification

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dc.contributor.author Bruzda, Joanna
dc.date.accessioned 2017-04-18T12:00:40Z
dc.date.available 2017-04-18T12:00:40Z
dc.date.issued 2016-12-28
dc.identifier.citation Dynamic Econometric Models, No. 1, Vol. 16, pp. 5-20
dc.identifier.issn 2450-7067
dc.identifier.other doi:10.12775/DEM.2016.001
dc.identifier.uri http://repozytorium.umk.pl/handle/item/4158
dc.description.abstract In the paper we present our initial results of an empirical verification of different methodologies of quantile forecasting used in operational management to calculate the re-order point or order-up-to level as well as the optimal order quantity according to the newsvendor model. The comparison encompasses 26 procedures including quantile regression, the basic bootstrap method and popular textbook formulas. Our results, obtained on the base of 30 time series concerning such diversified phenomena as supermarket sales, passenger transport and water and gas demand, point to the usefulness of regression medians, regression quantiles, bootstrap methods and the procedures available in the SAP ERP system.
dc.language.iso eng
dc.rights Attribution-NoDerivs 3.0 Poland
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nd/3.0/pl/
dc.subject LINLIN loss
dc.subject quantile forecasting
dc.subject quantile regression
dc.subject re-order point
dc.subject theta method
dc.title Quantile Forecasting in Operational Planning and Inventory Management – an Initial Empirical Verification
dc.type info:eu-repo/semantics/article


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