Jim Griffin (University College London) – Normalized Latent Measure Regression Models

Abstract: Normalized Latent Measure Models (NLMMs) are a framework for modelling and comparing similar probability distributions using mixtures of nonparametric distributions. In this talk, I will focus on density regression problems where the distributions are indexed by covariates. As well as introducing the models, I will discuss how identifiability, variable selection and overfitting can be addressed within a Bayesian framework to provide interpretable inferential methods. I will illustrate their use in a range of applications.