論文

査読有り
2016年

Application of an integer-valued autoregressive model to hit phenomena

Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
  • Yasuko Kawahata
  • ,
  • Tamio Koyama

開始ページ
2513
終了ページ
2517
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/BigData.2016.7840890
出版者・発行元
Institute of Electrical and Electronics Engineers Inc.

We propose a new model for hit phenomena. Our model is based on the Integer-Valued autoregressive model in form of a stochastic difference equation, and it describes behaviors of count data sequences. Utilizing our model, we give a theoretical formulation of the concept 'hit', and a systematic method deciding whether given time series count data contains 'hit'.

リンク情報
DOI
https://doi.org/10.1109/BigData.2016.7840890
ID情報
  • DOI : 10.1109/BigData.2016.7840890
  • SCOPUS ID : 85015155015

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