FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2058970686> ?p ?o ?g. }

• W2058970686 endingPage "61" @default.
• W2058970686 startingPage "31" @default.
• W2058970686 abstract "Exponential sum models are used frequently: in heat diffusion, diffusion of chemical compounds, time series in medicine, economics, physical sciences and technology. Thus it is important to find good methods for the estimation of parameters in exponential sums. In this paper we review and discuss results from the last forty years of research. There are many different ways of estimating parameters in exponential sums and model a fit criterion, which gives a valid result from the fit. We find that a good choice is a weighted two-norm objective function, with weights based on the maximum likelihood (ML) criterion. If the number of exponential terms is unknown, statistical methods based on an information criterion or cross-validation can be used to determine the optimal number. It is suitable to use hybrid Gauss–Newton (GN) and quasi-Newton algorithms to find the unknown parameters in the constrained weighted nonlinear least-squares (NLLS) problem formulated using an maximal likelihood (ML) objective function. The problem is highly ill conditioned and it is crucial to find good starting values for the parameters. To find the initial parameter values, a modified Prony method or a method based upon rewriting partial sums as geometrical sums is proposed." @default.
• W2058970686 created "2016-06-24" @default.
• W2058970686 creator A5014073701 @default.
• W2058970686 creator A5033224155 @default.
• W2058970686 date "2002-02-01" @default.
• W2058970686 modified "2023-10-16" @default.
• W2058970686 title "A review of the parameter estimation problem of fitting positive exponential sums to empirical data" @default.
• W2058970686 cites W1677105421 @default.
• W2058970686 cites W1968025045 @default.
• W2058970686 cites W1978516417 @default.
• W2058970686 cites W1984981424 @default.
• W2058970686 cites W1987878610 @default.
• W2058970686 cites W1997654672 @default.
• W2058970686 cites W1999966354 @default.
• W2058970686 cites W2000467776 @default.
• W2058970686 cites W2000629617 @default.
• W2058970686 cites W2002443936 @default.
• W2058970686 cites W2009422418 @default.
• W2058970686 cites W2016310312 @default.
• W2058970686 cites W2017327347 @default.
• W2058970686 cites W2018624971 @default.
• W2058970686 cites W2029947365 @default.
• W2058970686 cites W2038742368 @default.
• W2058970686 cites W2040226888 @default.
• W2058970686 cites W2040763577 @default.
• W2058970686 cites W2044270029 @default.
• W2058970686 cites W2044609813 @default.
• W2058970686 cites W2044779088 @default.
• W2058970686 cites W2046281089 @default.
• W2058970686 cites W2046915036 @default.
• W2058970686 cites W2051531012 @default.
• W2058970686 cites W2053653133 @default.
• W2058970686 cites W2054658115 @default.
• W2058970686 cites W2061781757 @default.
• W2058970686 cites W2062213220 @default.
• W2058970686 cites W2067526476 @default.
• W2058970686 cites W2069111276 @default.
• W2058970686 cites W2069660266 @default.
• W2058970686 cites W2072949851 @default.
• W2058970686 cites W2073649065 @default.
• W2058970686 cites W2076681846 @default.
• W2058970686 cites W2080708853 @default.
• W2058970686 cites W2081182772 @default.
• W2058970686 cites W2082050383 @default.
• W2058970686 cites W2082503230 @default.
• W2058970686 cites W2086035791 @default.
• W2058970686 cites W2088083240 @default.
• W2058970686 cites W2091042307 @default.
• W2058970686 cites W2122825283 @default.
• W2058970686 cites W2142635246 @default.
• W2058970686 cites W2152293455 @default.
• W2058970686 cites W2164422015 @default.
• W2058970686 cites W2171132099 @default.
• W2058970686 cites W2253451972 @default.
• W2058970686 cites W2313192059 @default.
• W2058970686 cites W2335076570 @default.
• W2058970686 cites W2509548214 @default.
• W2058970686 cites W2912430942 @default.
• W2058970686 cites W4235240667 @default.
• W2058970686 cites W4235737738 @default.
• W2058970686 cites W4240745653 @default.
• W2058970686 cites W4241740546 @default.
• W2058970686 cites W4250116122 @default.
• W2058970686 cites W4253920091 @default.
• W2058970686 cites W93780692 @default.
• W2058970686 doi "https://doi.org/10.1016/s0096-3003(00)00138-7" @default.
• W2058970686 hasPublicationYear "2002" @default.
• W2058970686 type Work @default.
• W2058970686 sameAs 2058970686 @default.
• W2058970686 citedByCount "69" @default.
• W2058970686 countsByYear W20589706862012 @default.
• W2058970686 countsByYear W20589706862013 @default.
• W2058970686 countsByYear W20589706862014 @default.
• W2058970686 countsByYear W20589706862015 @default.
• W2058970686 countsByYear W20589706862016 @default.
• W2058970686 countsByYear W20589706862017 @default.
• W2058970686 countsByYear W20589706862018 @default.
• W2058970686 countsByYear W20589706862019 @default.
• W2058970686 countsByYear W20589706862020 @default.
• W2058970686 countsByYear W20589706862021 @default.
• W2058970686 countsByYear W20589706862022 @default.
• W2058970686 countsByYear W20589706862023 @default.
• W2058970686 crossrefType "journal-article" @default.
• W2058970686 hasAuthorship W2058970686A5014073701 @default.
• W2058970686 hasAuthorship W2058970686A5033224155 @default.
• W2058970686 hasConcept C105795698 @default.
• W2058970686 hasConcept C126255220 @default.
• W2058970686 hasConcept C134306372 @default.
• W2058970686 hasConcept C14036430 @default.
• W2058970686 hasConcept C143724316 @default.
• W2058970686 hasConcept C151376022 @default.
• W2058970686 hasConcept C151730666 @default.
• W2058970686 hasConcept C167928553 @default.
• W2058970686 hasConcept C28826006 @default.
• W2058970686 hasConcept C33923547 @default.
• W2058970686 hasConcept C53638454 @default.
• W2058970686 hasConcept C78458016 @default.
• W2058970686 hasConcept C86803240 @default.

• next