A trust region SQP algorithm for equality constrained parameter estimation with simple parameter bounds. (English summary) Comput. Optim. Appl. 28 (2004), no. 1, 51–86. The authors introduce a new algorithm for a class of parameter estimation problems. They remark that due to the presence of unobservable variables, the parameter estimation problems may have non-unique solutions for these variables. These can also lead to singular or ill-conditioned Hessians and this may be responsible for slow or non-convergence of usual nonlinear programming algorithms. Here an algorithm is presented that leads to strong descent convergence to a stationary point. This algorithm is based on successive quadratic programming, keeping the steps in a trust region. The paper ends with a qualitative analysis and tests
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