Multiparametric Curve Fitting 14. Modus-Operandi Of The Least-Squares Algorithm Minopt

Title Alternative:Multiparametric curve fitting XIV. Modus operandi of the least-squares algorithm MINOPT
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dc.contributor.authorMilitký, Jiří
dc.contributor.authorMeloun, Milan
dc.date.accessioned2016-07-08
dc.date.available2016-07-08
dc.date.issued1993
dc.description.abstractHybrid least-squares algorithm MINOPT for a nonlinear regression is introduced. MINOPT from CHEMSTAT package combines fast convergence of the Gauss-Newton method in a vicinity of minimum with good convergence of gradient methods for location far from a minimum. Quality of minimization and an accuracy of parameter estimates for six selected models are examined and compared with different derivative least-squares methods of five commercial regression packages.en
dc.formattext
dc.identifier.doi10.1016/0039-9140(93)80333-M
dc.identifier.issn0039-9140
dc.identifier.scopus2-s2.0-0039211950
dc.identifier.urihttps://dspace.tul.cz/handle/15240/16555
dc.language.isoen
dc.publisherElsevier Science Bv
dc.relation.ispartofTalanta
dc.sourcej-scopus
dc.sourcej-wok
dc.titleMultiparametric Curve Fitting 14. Modus-Operandi Of The Least-Squares Algorithm Minopten
dc.title.alternativeMultiparametric curve fitting XIV. Modus operandi of the least-squares algorithm MINOPTen
dc.typearticle
local.accessaccess
local.citation.epage277
local.citation.spage269
local.departmentDepartment of Textile Materials
local.facultyFaculty of Textile Engineering
local.fulltextyes
local.identifier.pubmed18965627
local.identifier.wokA1993KU30900026
local.notenefunguje RIV
local.relation.issue2
local.relation.volume40
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