2007
DOI: 10.1145/1268776.1268782
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Algorithm 869

Abstract: ODRPACK (TOMS Algorithm 676) has provided a complete package for weighted orthogonal distance regression for many years. The code is complete with user selectable reporting facilities, numerical and analytic derivatives, derivative checking, and many more features. The foundation for the algorithm is a stable and efficient trust region Levenberg-Marquardt minimizer that exploits the structure of the orthogonal distance regression problem. ODRPACK95 was created to extend the functionality and usability of ODRPA… Show more

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Cited by 44 publications
(15 citation statements)
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“…17 and 28 were redone using the Al and Cu Hugoniots as established by Knudson et al 27 as appropriate and the results fit using Orthogonal Distance Regression (ODR). 29,30 We chose ODR (also referred to as Total Least Squares) over ordinary least-squares regression (OLS) to best capture the error in both the U S and u values since they were roughly of equal magnitude.…”
Section: Resultsmentioning
confidence: 99%
“…17 and 28 were redone using the Al and Cu Hugoniots as established by Knudson et al 27 as appropriate and the results fit using Orthogonal Distance Regression (ODR). 29,30 We chose ODR (also referred to as Total Least Squares) over ordinary least-squares regression (OLS) to best capture the error in both the U S and u values since they were roughly of equal magnitude.…”
Section: Resultsmentioning
confidence: 99%
“…The implicit nonlinear weighted orthogonal distance fitting was performed using ODRPACK95 (Zwolak et al 2007), which is an updated version of ODRPACK (Boggs et al 1989). This fitting routine takes into account the uncertainties in the photometry, extinction corrections, parallaxes, [Fe/H] values and periods.…”
Section: Monte Carlo Testsmentioning
confidence: 99%
“…Based on the background explained above, we selected the IgorPro software. 27) With respect to the nonlinear least-squares module, we used the Levenberg-Marquardt algorithm within the orthogonal distance regression library pack (ODR95), 33), 34) which is built into IgorPro.…”
Section: Selection Of the Programming Language And The Nonlinear Leasmentioning
confidence: 99%