Calculation of intrinsic and parameter-effects curvatures for nonlinear regression models

DOI10.1080/03610918308812333zbMath0519.65098OpenAlexW2094714767MaRDI QIDQ3668810

Douglas M. Bates, David C. Hamilton, Donald G. Watts

Publication date: 1983

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918308812333

zbMATH Keywords

QR decompositionorthogonal vectorsleast squares estimatesrotation of coordinatesbasis for normal acceleration spaceintrinsic curvature arraysnonlinear model-design-data set combinationparameter-effects

Mathematics Subject Classification ID

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

Related Items (3)

An alternative computational algorithm for calculating the nonlinearity of regression models with two parameters ⋮ Relative curvature measures of nonlinearity for time series models ⋮ A statistical approach to the forward kinematics nonlinearity analysis of Gough-Stewart mechanism

Uses Software

• LINPACK

Cites Work

• Accounting for intrinsic nonlinearity in nonlinear regression parameter inference regions
• Parameter transformations for improved approximate confidence regions in nonlinear least squares

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