Comparing Distributions by using Dependent Normalized Random-Measure Mixtures
用相依归一化随机测度混合模型比较分布
Summary A methodology for the simultaneous Bayesian non-parametric modelling of several distributions is developed. Our approach uses normalized random measures with independent increments and builds dependence through the superposition of shared processes. The properties of the prior are described and the modelling possibilities of this framework are explored in detail. Efficient slice sampling methods are developed for inference. Various posterior summaries are introduced…