Loosely coupled nonlinear least squares

DOI10.1016/0167-9473(92)90177-HzbMath0875.62281OpenAlexW2078692772WikidataQ58040125 ScholiaQ58040125MaRDI QIDQ2563597

Yuh-Wen Soo, Douglas M. Bates

Publication date: 10 November 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(92)90177-h

zbMATH Keywords

conditional linearityGolub-Pereyra algorithmKaufman algorithm

Mathematics Subject Classification ID

General nonlinear regression (62J02) Probabilistic methods, stochastic differential equations (65C99)

Related Items (4)

Effective sample size for spatial regression models ⋮ Multiresponse spline regression ⋮ Self‐Modeling for Two‐Dimensional Response Curves ⋮ Estimating reducible stochastic differential equations by conversion to a least-squares problem

Uses Software

• R
• LINPACK

Cites Work

• A Relative Offset Orthogonality Convergence Criterion for Nonlinear Least Squares
• A variable projection method for solving separable nonlinear least squares problems
• Approximation to Data by Splines with Free Knots
• Self Modeling Nonlinear Regression
• The Differentiation of Pseudo-Inverses and Nonlinear Least Squares Problems Whose Variables Separate
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