Before revision:  In particular, the lasso and elastic net linear regression models employ a double-exponential distribution in their prior , which results in some maximum-likelihood regression coefficients being identically zero. Because of their ability to simultaneously perform parameter estimation and variable selection, these models have become enormously popular .
After revision:  In particular, the lasso and elastic net linear regression models employ a double-exponential prior distribution on the model parameters to achieve regression shrinkage and variable selection, these models have become enormously popular .