¥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).