nonlinear least squaresmanifoldsMPFIT is a port to IDL of the non-linear least squares fitting program MINPACK-1. MPFIT inherits the robustness of the original FORTRAN version of MINPACK-1, but is optimized for performance and convenience in IDL. In addition to the main fitting engine, MPFIT,...
The usefulness of a "non-linear least-squares type algorithm" such as the Microsoft Excel Solver for response surface modeling of ionogenic solutes in reversed-phase liquid chromatography has been examined. The retention factors of adenosine, a typical ionogenic solute, in buffered mobile phases of...
MPFIT is a port to IDL of the non-linear least squares fitting program MINPACK-1. MPFIT inherits the robustness of the original FORTRAN version of MINPACK-1, but is optimized for performance and convenience in IDL. In addition to the main fitting engine, MPFIT, several specialized functions ...
Liu HM, Wei GL, Xu Z, Liu P, Li Y (2016) Quantitative analysis of Fe and Co in Co-substituted magnetite using XPS: the appli- cation of non-linear least squares fitting (NLLSF). Appl Surf Sci 389:438-446Liu, H.; Wei, G.; Xu, Z.; Liu, P.; Li, Y. Quantitative analysis ...
Non-linear least-squares fitting algorithm In order to derive the spectroscopic parameters from the experimental transmissivity data, a non-linear least-square fitting program was developed. The calculated spectra are compared with the observed spectra on a point-by-point basis. By minimizing the diff...
The non-linear least-squares utility is defined in package "o.a.c.math4.legacy.fitting.leastsquares".[2] This functionality lets the user provide * the (multivariate) function * the Jacobian matrix Do I understand correctly that you want to implement a utility that ...
The values evaluated by using the non-linear least-squares fitting for determination of Arrhenius parameters were A = 2.20 x 10(8) L mol(-1) s(-1... M Ohoka,S Misumi,M Yamamoto - 《Polymer Journal》 被引量: 4发表: 1999年 Analysis of the thermal decomposition of azo-peroxyesters by...
The least-squares method is most widely used for fitting non-linear models to such collected data. It is here shown that due to the non-Gaussian characteristics of the noise in the absorbance data, the least-squares method is not optimal and introduces a systematic bias to the estimated ...
estimate from the first step is re-entered as the initial guess of the desired solution into an EEG least squares fitting procedure with Twomey ... Z Liu,F Kecman,B He - 《Clinical Neurophysiology》 被引量: 64发表: 2006年 From Angular Manifolds to the Integer Lattice: Guaranteed Orientation...
Figure 2 shows 3D reconstructions of the target scene obtained by combining the depth and intensity information retrieved using the non-linear least squares fitting method. The results have been cropped to the scene (228 by 228 pixels). We apply a correction to the retrieved depth profile to ac...