Penalized Least Square Estimator for Non-Linear Models
1 Geomatics College，Shandong University of Science and Technology，579 Qianwangang Road, Qingdao 266510， China
Abstract In the geodesy，many models are nonlinear.The classical methods dealing with nonlinear models are either linear approximations using the approximation value of parameters or iterations.Some nonlinear models can not be linearized and are very difficult to evaluate precision of estimators by the methods.To solve the problems，the penalized least square estimator for nonlinear models were presented and related estimation formulas supported.That is the key lying in that substituting the nonparameters of semiparametric models for the Taylor expansion reminders.The results calculated with the method show that the method is effective for the nonlinear models.
Key words ：
nonlinear model
nonlinearity
semi-parametric model
penalized least square estimator
adjustment
Received: 12 February 2014
Published: 06 February 2015
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