 Penalized least-squares estimator

A penalized least-squares estimator balances squared error with a nonnegative penalty $J$. The Lasso uses the coefficient ${\ell }_1$ norm; graph total variation denoising uses the ${\ell }_1$ norm of endpoint differences. The choice of normalization of the squared loss changes the numerical tuning parameter.