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- W137309310 abstract "Multiway spectroscopic measurementsare collections of spectra represent- ing a photophysical system at many different times or other conditions. Simul- taneous analysis of such measurements in terms of a parametric model (global analysis in the photophysical literature) provides insight into the dynamics of the underlying system. Measurementsrepresent a superposition of the contributions of ncomp spec- trally distinct components. The concentration and spectral property of each component may be represented as column l of matrices C and E, respectively, where C is of dimension nt×ncomp, E is of dimension nl×ncomp, nt is the num- ber of times or other conditions at which spectra were measured, and nl is the number of (wavelength or wavenumber) points by which spectra are represented. The basic superposition model for such measurements is � = CE T. Given �, the inverse problem of recovery of the entries of C or E in terms of physically significant parameters (descriptive of, e.g., the decay rate of a component, or the location of the maximum of a spectrum) is often of inter- est. Adequate parameterizations of either C or E are nonlinear, and are of- ten hierarchical in nature. For example, column l of C may be described as Cl = exp( klt) gaus(µ,�), where kl is a decay rate parameter, t is time, is convolution and µ andare location and width parameters, respectively. Parameters µ andmay in turn be described as nonlinear functions of e.g., wavelength �, so that Cl is wavelength-dependent and the model description is hierarchical (1). Once a model is parameterized for C or E, the entries of the re- maining matrix may often be treated as conditionally linear, taking advantage of the separable model form (2). Intrinsically nonlinear parameter estimates may be derived by nonlinear regression, which has the advantage of returning parameter confidence estimates valuable in model interpretation and validation (3). R has been used to prototype a problem-solving environment for paramet- ric modeling of multiway spectroscopic measurements. Hierarchical models for multiway spectroscopic measurements find natural description as a hierarchy of S4 classes. S4 methods provide a means to differentiate the treatment of many different model types while maintaining uncomplicated calling code. The nls and numericDeriv functions provide a fast basis for nonlinear regression. An extended version of the problem-solving environment for public release is being developed as the package TIMP." @default.
- W137309310 created "2016-06-24" @default.
- W137309310 creator A5030192190 @default.
- W137309310 date "2006-01-01" @default.
- W137309310 modified "2023-09-26" @default.
- W137309310 title "TIMP: A package for parametric modeling of multiway spectroscopic measurements" @default.
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- W137309310 hasPublicationYear "2006" @default.
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