Overview Maximum likelihood estimation (MLE) is a gold standard estimation procedure in non-Bayesian statistics, and the likelihood function is central to Bayesian statistics (even though it is not maximized in the Bayesian paradigm). MLE may be unpenalized (the standard approach) or various penalty functions such as L1 (lasso, absolute value penalty), and L2 (ridge regression; quadratic) penalties may be added to the log-likelihood to achieve shrinkage (aka regularization). I have been doing...
