Nonparametric Time Series Modeling based on Fuzzy Data

Document Type : Original Paper


1 Department of Statistics, Payame Noor University, Tehran 19395-4697, Iran

2 Department of Statistics, University of Birjand, Birjand 615-97175, Iran.


In this paper, a nonparametric time series model based on fuzzy observations is presented.
Fuzzy prediction values are estimated using the generalization of the Nadaraya-Watson method in a fuzzy environment. An algorithm for achieving autoregressive order and optimal bandwidth is stated and then criteria are introduced to evaluate the prediction values. In the following, the performance of the proposed model is examined and analyzed using real data. The effectiveness of the proposed model is also compared with the other time series models with fuzzy data.


Main Subjects

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