An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
归一化常数难以计算时的高效马尔可夫链蒙特卡洛方法
Maximum likelihood parameter estimation and sampling from Bayesian posterior distributions are problematic when the probability density for the parameter of interest involves an intractable normalising constant which is also a function of that parameter. In this paper, an auxiliary variable method is presented which requires only that independent samples can be drawn from the unnormalised density at any particular parameter value. The proposal distribution is constructed so…