Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method
Arshia Amiri,
Mohamad Bakhshoodeh and
Bahaeddin Najafi
MPRA Paper from University Library of Munich, Germany
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.
Keywords: Price; Geostatistical model; Kiriging; Inverse distance weighting; Winter’s method; Adaptive neuro fuzzy inference system; Potatoes; Onions; Iran (search for similar items in EconPapers)
JEL-codes: C53 Q1 (search for similar items in EconPapers)
Date: 2011-10-13
New Economics Papers: this item is included in nep-cis, nep-cmp and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/34093/1/MPRA_paper_34093.pdf original version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:34093
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().