2.3.4 Ridge Regression Model
Ridge regression33, is a dedicated to total linear
biased estimation of regression data analysis method, is in essence a
kind of improved least squares estimation method, by giving up the
unbiasedness of least-square method, in order to lose some information,
to reduce the accuracy at the expense of regression coefficient is more
practical, more reliable regression method, the fitting of pathological
data than the least square method. Ridge regression model is a widely
used model34. Ridge regression is to artificially add
a non-negative factor k to the main diagonal elements of the information
matrix composed of independent variables, so that the matrix determinant
is not zero, so as to reduce the error of regression coefficient
estimation, improve the estimation accuracy and the model
stationarity.Ridge regression can repair ill-conditioned matrix and
achieve better results.
Its
implified diagram is shown in Figure 7.