文摘
In this work we study, as the temperature goes to zero, the oscillation of a family of Gibbs measures around LASSO estimator. We derive new criteria for estimating LASSO, choosing the proposal distribution and the temperature in Metropolis–Hastings algorithm. Finally we apply these results to analyse the convergence of Metropolis–Hastings and simulated annealing algorithms.