Bayesian Lasso. The standard lasso uses an L1 regularisation penalty to achieve sparsity in regression. May 21 2019 BLasso x y nmax 10000 EB TRUE a 1 b 1 printit FALSE.
In the Bayesian view of lasso regression the prior distribution of the regression coefficients is Laplace double exponential with mean 0 and scale where is the fixed shrinkage parameter and. Sep 05 2014 The Bayesian Lasso Journal of the American Statistical Association 103 482 681-686 DOI. For more details see lassoblm.
Moreover the structure of the hierarchical model provides both Bayesian and likelihood methods for selecting the Lasso parameter.
Moreover the structure of the hierarchical model provides both Bayesian and likelihood methods for selecting the Lasso parameter. The Bayesian Lasso provides interval estimates Bayesian credible intervals that can guide variable selection. The algorithm implemented by this function is identical to that described therein with the exception of an added option to use a Rao-Blackwellized sample of 2 with integrated out for. Moreover the structure of the hierarchical model provides both Bayesian and likelihood methods for selecting the Lasso parameter.
