The Use of Partial Least Squares Method To Remove Multicollinearity

In this research the estimation of the regression parameters was clarified using least squares and partial least squares compared with the normal method in terms of its ability to be free from the problem of Multicollinearity between the predictive variables, the first method is the possibility of a regression analysis of several response variables with a number of predictive variables at the same time, was the application of both methods on the data production of cement as described in the manufacture Material of cement, either predictive variables for the response variables by cement and clinker, dust and solid waste.