Regression model for dam deformation based on principal component and semi-parametric analysis

Principal component analysis(PCA) is a solution to the multicollinearity problem of dam regression models.However,uninformative principal components(PCs) may lead to the failure prediction of dam deformation.Thus a hybrid regression model using semi-parametric regression and PCA is proposed,where the PCs with the highest variance are treated as the semi-parametric component;the remaining PCs and model errors are treated as the non-parametric component to be estimated.The hybrid model is tested using the field observations of a dam in China.The result shows the hybrid model can circumvent the multicollinearity of dam causative effects and the ill-conditioned problem in semi-parametric penalized least squares regression.A comparative study with traditional PC regression and stepwise regression demonstrate the superior performance for dam deformation prediction.