Statistical Inference using Stochastic Switching Models for the Discrimination of Unobserved Non-Price Promotion

  • Sato Tadahiko
    Graduate School of Business Science, University of Tsukuba
  • Higuchi Tomoyuki
    Research Organization of Information and Systems, The Institute of Statistical Mathematics
  • Kitagawa Genshiro
    Research Organization of Information and Systems, The Institute of Statistical Mathematics

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Other Title
  • マルコフ切換モデルによる観測されない非価格プロモーション実施の有無の統計的推測法
  • マルコフ キリカエ モデル ニ ヨル カンソク サレナイ ヒカカク プロモーション ジッシ ノ ウム ノ トウケイテキ スイソクホウ

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It is known that an execution of price and/or a non-price promotion has a strong influence on the sales of a brand sold in a supermarket. Usually, we can easily obtain information on a price promotion from a POS data. On the other hand, unless investigator collects information on an execution of non-price promotion in every retail store, we can not obtain such information. In this paper, we consider a problem to identify whether or not non-price promotion is conducted. We treat a non-price promotion execution/non-execution as a state variable. An unknown stationary probability matrix is assumed to describe the probability of a transition between states. Each state is characterized by a different stationary time series model with unknown parameters. An objective of the analysis is to identify the model and to assign a probability model for each state at each time instant. Finally, we give a high precision estimator of a past non-price promotion based on the proposal model.

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