论文标题
具有可交换长度变量的破坏性过程
Stick-breaking processes with exchangeable length variables
论文作者
论文摘要
我们的研究对象是具有可交换长度变量的棒状过程的一般类别。这些概括了众所周知的贝叶斯非参数先验，沿未经探索的方向。我们提供的条件可以确保各自的物种采样过程适当，并且相应的先验具有全部支持。对于丰富的子类，我们解释了如何通过调整单个$ [0,1] $的价值参数，可以调制权重的随机排序，并可以恢复dirichlet和几何先验。得出了潜在分配变量分布的一般公式，并为密度估计目的提出了MCMC算法。
Our object of study is the general class of stick-breaking processes with exchangeable length variables. These generalize well-known Bayesian non-parametric priors in an unexplored direction. We give conditions to assure the respective species sampling process is proper and the corresponding prior has full support. For a rich sub-class we explain how, by tuning a single $[0,1]$-valued parameter, the stochastic ordering of the weights can be modulated, and Dirichlet and Geometric priors can be recovered. A general formula for the distribution of the latent allocation variables is derived and an MCMC algorithm is proposed for density estimation purposes.
