Convergence analysis of a proximal Gauss-Newton method

Saverio Salzo () and Silvia Villa ()

Computational Optimization and Applications, 2012, vol. 53, issue 2, 557-589

Abstract: An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Convergence results of local type are obtained, as well as an estimate of the radius of the convergence ball. Some applications for solving constrained nonlinear equations are discussed and the numerical performance of the method is assessed on some significant test problems. Copyright Springer Science+Business Media, LLC 2012

Keywords: Gauss-Newton method; Penalized nonlinear least squares; Proximity operator; Lipschitz conditions with L average (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10589-012-9476-9

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