Modeling for life cycle cost by using DEA to optimizing principal components regression

The regression statistical modeling,one of the modeling methods of the life cycle cost(LCC),is used for estimating the average trend of the data essentially,which can not avoid the pro-blem about obtaining the wrong model according to the error data.Therefore,the improved principal component regression(PCR) by means of data envelopment analysis(DEA) was proposed to overcome this problem,which could evaluate the efficiency of the data and remove the inefficiency data for PCR modeling.The new approach can overcome the effect of the disturbed data in filtering principal components in the independent variables.Compared with the method of PCR and partial least squares regression(PLSR),the improved PCR with DEA is much higher in precision.