主成分估计采用的方法是将原来的回归自变量变换到另一组变量，即主成分，选

主成分估计采用的方法是将原来的回归自变量变换到另一组变量，即主成分，选择其中一部分重要的主成分作为新的自变量（此时丢弃了一部分，影响不大的自变量，这实际达到了降维的目的），然后用最小二乘法对选取主成分后的模型参数进行估计，最后再变换回原来的模型求出参数的估计。

結果 (英文) 1:

Main components estimated used of method is will original of return since variable transform to another a group variable, that main components, select which part important of main components as new of since variable (at discarded has part, effect is unlikely to of since variable, this actual reached has drop dimension of purpose), then with minimum II multiplication on selected main components Hou of model parameter for estimated, last again transform back original of model seeking out parameter of estimated.

結果 (英文) 2:

Principal component estimation method used is the return of the original argument converted to another set of variables, that is the main component, select one of the important part of the main component as a new independent variable (in this case a portion of discarded little impact argument, this dimensionality reduction actually achieved the goal), followed by the least squares method to select the model parameters were estimated after the main component, and finally converted back to the original model parameter estimation is obtained.

結果 (英文) 3:

The principal component estimation method is to transform the original variable to another set of variables, namely principal component, choose one of the important part of the principal component as the new variable (now abandoned part of small, independent variables, which actually reach the goal of dimension reduction), then the model parameters selection of principal components the estimated by least square method, then transform back to the original model for parameter estimation.