Principal Components Estimate Of Regression Coefficient Of Multivariate Linear Regression Model

Principal component analysis is widely applied in these fields such as: Social economy,Enterprises management, geology, biochemistry, medicine etc. Is estimate is the most widelyapplied in linear model regression of unbiased test, but in case of many independent variable,biased estimate has better result. To estimate linear regression model regression withprincipal component is also called Biased, which is similar to Ridge estimate and Steinestimate. They're one of linear changes of the LS estimate.On the base of the principal component estimation is built. Therefore, afterconsulting many editions of principal component analysis, the author adopt another method toanalyze that is get rid of the equivalent characteristic root. At the same time, to go furthersummarize the overall principal component , character of sample principalcomponent and answering method.Principal component estimation is based on unary linear model regression coefficientof principal component estimation to multivariate linear model regressions coefficient ofprincipal component estimation, and then parallel calculation some results, which makethe principal component bring into full play of function and form perfect system in multivariatelinear model regressions coefficient estimation.