with the Lasso algorithm in the linear least squared settings. We show that the fitted transformation matrix is close to …

approach with locally weighted regression to achieve sparse models. Specifically, the lasso is a shrinkage and selection method … for linear regression. We present an algorithm that embeds lasso in an iterative procedure that alternatively computes … weights and performs lasso-wise regression. The algorithm is tested on three synthetic scenarios and two real data sets …

with Bayesian Markov Chain Monte Carlo. The resulting model is equivalent to the frequentist lasso procedure. A … covariates is provided by the approach. An implementation of the lasso procedure for binary quantile regression models is …