文献类型：期刊文献

英文题名：Prediction intervals of an alternative formulation of partial least squares algorithm

作者：Lin, Weilu[1]; Martin, Elaine[2]

机构：[1] State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China; [2] School of Chemical Engineering and Advanced Materials, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom

年份：2011

起止页码：461

外文期刊名：2011 International Symposium on Advanced Control of Industrial Processes, ADCONIP 2011

收录：EI(收录号：20113014181563)

语种：英文

外文关键词：Inverse problems - Iterative methods - Forecasting - Least squares approximations

摘要：The prediction interval is an important property when applies the partial least squares (PLS) to virtual sensor applications. In this work, we propose a new formulation of PLS, such that after projecting out score vectors, the estimated coefficient matrix is obtained as the product of pseudo inverse of the predictor matrix and corresponding weighting matrices. The new formulation, which facilitates the calculation of Jacobian matrix and can be extended to multivariate PLS, is proved to be equivalent to the nonlinear iterative partial least squares (NIPALS). The prediction interval of the algorithm is developed based on the Jacobian of singular vectors. Industrial case studies demonstrate the utility of the algorithm for univariate PLS. ? 2011 Zhejiang University.