Control Variates for the Metropolis–Hastings Algorithm
Control Variates for the Metropolis–Hastings Algorithm
Abstract. We propose new control variates for variance reduction in estimation of mean values using the Metropolis–Hastings algorithm. Traditionally, states that are rejected in the Metropolis–Hastings algorithm are simply ignored, which intuitively seems to be a waste of information. We present a setting for construction of zero mean control variates …