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Application of penalized least squares estimation in height anomaly

GAO Ning①,GAO Cai-yun①,XU Chang-hai②(①Department of Survey & Urban Spatial Information Engineering,Henan University of Urban Construction,Henan Pingdingshan 467044,China;②Department of Geography and Environment Science,Suzhou College,Suzhou 234000,China)  
The model errors exist inevitably in conventional least square fitting model of height anomaly,this article proposed that model error could be dealt with as nonparametric information using penalized least squares and discussed the effect of Regularizer R and Smoothing Parameter α on the results of fitting.Through the research on the solution of the Smoothing Parameter,a method of function Xu(α)was presented,and experimented on a GPS leveling measurement data.The Results showed that penalized least squares is better than least-square method in determining height anomaly.
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