¥LASSO (Least Absolute Shrinkage and Selection Operator) developed in
multiple regression to deal with multicollinearity.
¥A compromise between variable selection and biased regression. Shrinks
some regression coefficients exactly to
zero.
¥Adaptation to PCA: to the usual optimisation problem add an extra
constraint (Jolliffe, Trendafilov & Uddin,
2003).