Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/95785
Type: Artigo de periódico
Title: Serfit: An Algorithm To Forecast Mineral Trends
Author: Suslick S.B.
Harris D.P.
Allan L.H.E.
Abstract: A PASCAL computer program, named SERFIT, facilitates the identification of trend model for long-term forecasting and the estimation of model parameters. Model identification is achieved through the computation of slope characteristics from mineral data time series. The trend models generated by the program are: linear, normal, lognormal, and modified exponentials: simple-modified exponential, logistic, derivative logistic, Gompertz, and derivative Gompertz. Parameters of the family of modified exponential models are estimated using Mitscherlich's regression, which is based upon the maximum likelihood method and provides a probability structure for the models. SERFIT is demonstrated on U.S. petroleum production and world copper consumption data. © 1995.
Editor: 
Rights: fechado
Identifier DOI: 10.1016/0098-3004(94)00105-4
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0029482640&partnerID=40&md5=2ce66644733728db0e06d9536017532c
Date Issue: 1995
Appears in Collections:Unicamp - Artigos e Outros Documentos

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