Unbiased and consistent nested sampling via sequential Monte Carlo
通过序贯蒙特卡洛实现无偏且一致的嵌套采样
Abstract We introduce a new class of sequential Monte Carlo methods which reformulates the essence of the nested sampling (NS) method of Skilling in terms of sequential Monte Carlo techniques. Two new algorithms are proposed: nested sampling via sequential Monte Carlo (NS-SMC) and adaptive nested sampling via sequential Monte Carlo (ANS-SMC). The new framework allows convergence results to be obtained in the setting when Markov chain Monte Carlo (MCMC) is used to produce new…