Numerical algorithms for solving nonlinear l -norm estimation problems: Part i - a first-order gradient algorithm for well-conditioned small residual problems

DOI10.1080/03610918608812542zbMath0608.62079OpenAlexW2084025910MaRDI QIDQ3747539

René Gonin

Publication date: 1986

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

Full work available at URL: https://doi.org/10.1080/03610918608812542

zbMATH Keywords

nonlinear parameter estimationnonlinear least squaresL sup p normextension of the classical Gauss-Newton methodfirst-order gradient algorithmwell-conditioned small residual problems

Mathematics Subject Classification ID

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

Related Items (5)

Diagnostics for nonlinear \(L_ p\)-norm estimation ⋮ Total least squares fitting Bass diffusion model ⋮ Numerical algorithms for solving nonlinearL_р-norm estimation problems: part II - a mixture method for large residual and illo-conditioned problems ⋮ Numerical algorithms for nonlinear \(L_p\)-norm problem and its extreme case ⋮ Discrete total \({\l}_p\)-norm approximation problem for the exponential function

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