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Semi-Fuzzy Time Series for Robust Parameters Estimation

    Authors

    • Abdul Majid H. Alnasser
    • Taher R. Dekheel
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Abstract

The presence of outliers in data influences not only in diagnostic model, but exceed to parameters estimation. So the goal of this paper is to make the autocorrelation coefficient robust against outliers to estimate parameters which will be robust depending on those coefficients. This goal is achieved by two suggestions depending on Fuzzy Logic which suggests estimation procedure to estimate autocorrelation coefficients called Semi-Fuzzy Pearson coefficient ,and suggests another one called Semi-Fuzzy Kendall , to use it to estimate the autocorrelation coefficients which will be used in parameter estimation.

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AL-Qadisiyah Journal  For Administrative and Economic sciences
Volume 14, Issue 1
March 2013
Pages 129-151
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How to cite
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  • EndNote
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Statistics
  • Article View: 167
  • PDF Download: 103

APA

Majid H. Alnasser, A., & R. Dekheel, T. (2013). Semi-Fuzzy Time Series for Robust Parameters Estimation. AL-Qadisiyah Journal For Administrative and Economic sciences, 14(1), 129-151.

MLA

Abdul Majid H. Alnasser; Taher R. Dekheel. "Semi-Fuzzy Time Series for Robust Parameters Estimation". AL-Qadisiyah Journal For Administrative and Economic sciences, 14, 1, 2013, 129-151.

HARVARD

Majid H. Alnasser, A., R. Dekheel, T. (2013). 'Semi-Fuzzy Time Series for Robust Parameters Estimation', AL-Qadisiyah Journal For Administrative and Economic sciences, 14(1), pp. 129-151.

VANCOUVER

Majid H. Alnasser, A., R. Dekheel, T. Semi-Fuzzy Time Series for Robust Parameters Estimation. AL-Qadisiyah Journal For Administrative and Economic sciences, 2013; 14(1): 129-151.

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