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Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method

Author

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  • Amiri, Arshia
  • Bakhshoodeh, Mohamad
  • Najafi, Bahaeddin

Abstract

This paper, we studied the ability of geostatistical models (ordinary kriging (OK) and Inverse distance weighting (IDW)), adaptive neuro-fuzzy inference system (ANFIS) and Winter method for prediction of seasonality in prices of potatoes and onions in Iran over the seasonal period 1986_2001. Results show that the best estimators in order are winter method, ANFIS and geostatistical methods. The results indicate that Winter and ANFIS had powerful results for prediction the prices while geostatistical models were not useful in this respect.

Suggested Citation

  • Amiri, Arshia & Bakhshoodeh, Mohamad & Najafi, Bahaeddin, 2011. "Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method," MPRA Paper 34093, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:34093
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Price; Geostatistical model; Kiriging; Inverse distance weighting; Winter’s method; Adaptive neuro fuzzy inference system; Potatoes; Onions; Iran;
    All these keywords.

    JEL classification:

    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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