Demonstration Code for Nested Dirichlet Process

Question

My question is about how to implement the nested Dirichlet process (NDP) with R code.

The NDP is suitable for clustering over distributions and simultaneously clustering within a distribution. Rodriguez et al. (2008) provided a simulation example to demontrate the ability of the NDP to distinguish different distributions. I am trying to learn this approach by reproducing the results for this example. But failed to do so because I cannot understand well how the base distribution is related to the mixture components.

The simulation example used a normal inverse-gamma distributioin, NIG(0,0.01,3,1), as the base distribution. But the four different distributions are:

The algorithm provided in Section 4 (Rodriguez et al.,2008, p.1135) was used to do the simulation. I have problem to understand and execute this algorithm, especially step 5:

Can you please provide a sample code to demonstrate this algorithm? Your help is highly appreciated!

Answer 1

我自己无法进行编码，但是我发现了一篇最近使用精确推理而不是截断近似进行模拟的论文。我认为它可能对像我这样感兴趣的其他人有所帮助，所以我在这里发布了该论文的链接。

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我喜欢这篇论文的好处是它写得很好并且有源代码（在R中）让我更好地理解这种方法。