Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method
AbstractThis 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 34093.
Date of creation: 13 Oct 2011
Date of revision:
Price; Geostatistical model; Kiriging; Inverse distance weighting; Winter’s method; Adaptive neuro fuzzy inference system; Potatoes; Onions; Iran;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-10-22 (All new papers)
- NEP-CIS-2011-10-22 (Confederation of Independent States)
- NEP-CMP-2011-10-22 (Computational Economics)
- NEP-FOR-2011-10-22 (Forecasting)
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