Properties of nested sampling
Properties of nested sampling
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DOI：
10.1093/biomet/asq021
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发表时间：
2010-09-01
期刊：
影响因子：
2.7
通讯作者：
Robert, Christian P.
中科院分区：
文献类型：
--
作者：
Chopin, Nicolas;Robert, Christian P.
嵌套抽样是一种近似边际似然的模拟方法。我们建立了嵌套抽样有一个近似误差，该误差在标准蒙特卡洛速率下消失，并且该误差是渐近高斯的。结果表明，嵌套抽样近似的渐近方差通常随参数的维数线性增长。讨论了嵌套抽样在实际问题中的适用性和效率，并将其与目前两种计算边际似然的方法进行了比较。最后，我们提出了一种扩展，避免了使用马尔可夫链蒙特卡罗模拟来获得模拟点。
Nested sampling is a simulation method for approximating marginal likelihoods. We establish that nested sampling has an approximation error that vanishes at the standard Monte Carlo rate and that this error is asymptotically Gaussian. It is shown that the asymptotic variance of the nested sampling approximation typically grows linearly with the dimension of the parameter. We discuss the applicability and efficiency of nested sampling in realistic problems, and compare it with two current methods for computing marginal likelihood. Finally, we propose an extension that avoids resorting to Markov chain Monte Carlo simulation to obtain the simulated points.