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Building Fuzzy Random Autoregression Model and Its Application

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 15)

Abstract

The purpose of economic analysis is to interpret the history, present and future economic situation based on analyzing economical time series data. The autoregression model is widely used in economic analysis to predict an output of an index based on the previous outputs. However, in real-world economic analysis, given the co-existence of stochastic and fuzzy uncertainty, it is better to employ a fuzzy system approach to the analysis. To address regression problems with such hybridly uncertain data, fuzzy random data are introduced to build the autoregression model. In this paper, a fuzzy random autoregression model is introduced and to solve the problem, we resort to some heuristic solution based on σ-confidence intervals. Finally, a numerical example of Shanghai Composite Index is provided.

Keywords

fuzzy autoregression model fuzzy random data fuzzy random autoregression model time series data confidence interval 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lu Shao
    • 1
  • You-Hsi Tsai
    • 1
  • Junzo Watada
    • 1
  • Shuming Wang
    • 1
  1. 1.Graduate School of Information, Production and SystemsWaseda UniversityWakamatsuJapan

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