I implelemented a Gibbs sampler for Bayesian Lasso [1] in R.

Bayesian Lasso is a fully Bayesian approach for sparse linear regression by assuming independent Laplace (a.k.a. double exponential) priors for each regression coefficient.

**Usage Example:**

library(lars)

data(diabetes)

x <- scale(diabetes$x)

y <- scale(diabetes$y)

betas <- gibbsBLasso(x, y, max.steps = 100000)

**R Code:**

gibbsBLasso.R

**References:**

[1] Park, Trevor and Casella, George. The Bayesian Lasso. *Journal of American Statistical Association*. 103(482):681-686. 2008.