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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.



Item Type: MPRA Paper -

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

Language: English-

Keywords: Price; Geostatistical model; Kiriging; Inverse distance weighting; Winter’s method; Adaptive neuro fuzzy inference system; Potatoes; Onions; Iran-

Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - AgricultureC - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods-





Autor: Amiri, Arshia

Fuente: https://mpra.ub.uni-muenchen.de/34093/



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