Preprint Article Version 1 This version is not peer-reviewed

Forecasting Algorithms for Recurrent Patterns in Consumer Demand

Version 1 : Received: 24 August 2017 / Approved: 25 August 2017 / Online: 25 August 2017 (08:21:40 CEST)

How to cite: Boiko, T.; Karpenkov, O.; Rakhimberdiev, B. Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints 2017, 2017080086 (doi: 10.20944/preprints201708.0086.v1). Boiko, T.; Karpenkov, O.; Rakhimberdiev, B. Forecasting Algorithms for Recurrent Patterns in Consumer Demand. Preprints 2017, 2017080086 (doi: 10.20944/preprints201708.0086.v1).

Abstract

In this paper we develop a forecasting algorithm for recurrent patterns in consumer demand. We study this problem in two different settings: pull and push models. We discuss several features of the algorithm concerning sampling, periodic approximation, denoising and forecasting.

Subject Areas

seasonality; forecasting; pull and push models; denoising

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