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AuthorAouni, Belaid
AuthorColapinto, Cinzia
AuthorTorre, Davide La
Available date2023-12-28T10:30:51Z
Publication Date2015-01-01
Publication NameInternational Journal of Multicriteria Decision Making
Identifierhttp://dx.doi.org/10.1504/IJMCDM.2015.071251
CitationAouni, B., Colapinto, C., & Torre, D. L. (2015). Parameter estimation through the weighted goal programming model. International Journal of Multicriteria Decision Making, 5(3), 263-273.‏
ISSN2040106X
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84940529269&origin=inward
URIhttp://hdl.handle.net/10576/50664
AbstractMany models in economics, management and finance can be described in terms of nonlinear dynamical systems which usually depend on some unknown parameters. To conduct a long-run behaviour analysis of these models it is of paramount importance to establish efficient and accurate parameter estimation techniques. Today many sophisticated nonlinear model estimation, selection and testing approaches are available and reliable. However, when the nonlinear dynamical systems take the form of differential equations, many of them fail and it is required to use more advanced techniques. The aim of this paper is to present a weighted goal programming formulation for estimating the unknown parameters of dynamical models described in terms of differential equations. The method is illustrated through two different applications to population dynamics (Malthus model) and innovation diffusion (Bass model).
Languageen
PublisherInderscience Publishers
SubjectBass model
Malthus model
Parameter estimation
Weighted goal programming model
TitleParameter estimation through the weighted goal programming model
TypeArticle
Pagination263-273
Issue Number3
Volume Number5
dc.accessType Abstract Only


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