Publication | Closed Access
The Estimation of Parameters in Nonlinear, Implicit Models
490
Citations
14
References
1973
Year
Mathematical ProgrammingParametric ProgrammingParameter IdentificationParameter EstimationEngineeringApproximation TheoryImplicit ModelsMinimization ProblemNonlinear Algebraic ModelsConstrained OptimizationStatistical InferenceInverse ProblemsNonlinear OptimizationPublic HealthEstimation TheoryFunctional Data AnalysisStatisticsMaximum Likelihood Principle
The estimation of parameters in nonlinear algebraic models is considered for a general class of problems. Included are problems where both the independent and dependent variables are subject to error and problems where the model is algebraically implicit. The maximum likelihood principle leads to an equality constrained minimization problem. An algorithm to achieve this minimization is obtained through the use of Lagrange multipliers.
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