Database Reference
In-Depth Information
6.4 Additional Regression Models
In the case of multicollinearity, it may make sense to place some restrictions on
the magnitudes of the estimated coefficients.
Ridge regression
, which applies a
penalty based on the size of the coefficients, is one technique that can be applied. In
fitting a linear regression model, the objective is to find the values of the coefficients
that minimize the sum of the residuals squared. In ridge regression, a penalty term
proportional to the sum of the squares of the coefficients is added to the sum of the
residuals squared.
Lasso regression
is a related modeling technique in which the
penalty is proportional to the sum of the absolute values of the coefficients.
Only binary outcome variables were examined in the use of logistic regression. If
the outcome variable can assume more than two states,
multinomial logistic
regression can be used.
