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2012 5th Romania Tier 2 Federation Grid, Cloud & High Performance Computing Science (RQLCG)

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Quantitative conditioning criteria in bayesian automatic adaptive quadrature

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Quantitative conditioning criteria in bayesian automatic adaptive quadrature

Content Provider	IEEE Xplore Digital Library
Author	Adam, G. Adam, S.
Copyright Year	2012
Description	Author affiliation: Lab. of Inf. Technol., Joint Inst. for Nucl. Res., Dubna, Russia (Adam, G.; Adam, S.)
Abstract	Quantitative criteria enabling Bayesian inferences on the integrand conditioning over monotonicity intervals defined on integrand profiles obtained within the process of building the subrange binary tree associated to the numerical solution of a Riemann integral by automatic adaptive quadrature are derived. The theoretically obtained admissible relative variation bounds of the first order divided differences of the integrand around an abscissa belonging to the monotonicity interval put on firm ground previously reported empirical results.
Sponsorship	IEEE Romania Sect.
Starting Page	35
Ending Page	38
File Size	199848
Page Count	4
File Format	PDF
ISBN	9781467322423
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-25
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Natl Inst for Research
Subject Keyword	Floating point degree of precision Automatic adaptive quadrature Local quadrature rule Subrange binary tree Bayesian inference Integrand profile Well-conditioning criteria
Content Type	Text
Resource Type	Article

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