病态加权最小二乘混合模型的k-Liu估计解法OA北大核心CHSSCDCSSCICSTPCD

This paper synthesizes weighted multi-source observation model and least square mixed model,and combines two biased estimation algorithms to get a combined biased estimation algorithm.A new biased estimation—k-Liu estimation is formed by using ridge estimation and Liu estimation,which can effectively reduce the mean square error of parameter estimation while re-sisting the morbid coefficient matrix of normal equation.By constructing the objective function,the general solution formula,mean square error formula and cofactor calculation formula of the parameters of the k-Liu estimation in the morbid least squares mixed model are derived;the calculation formula of the correction factor in the k-Liu estimation is derived,and the ridge parameters are determined by the generalized cross-validation method.Finally,a variety of estimation methods are used for the calculation of ex-amples to draw the conclusion that the k-Liu estimation can further improve the calculation accuracy of the mixed least squares model.