STA 290 Seminar Series
DATE: Thursday, April 13th 2017, 4:10pm
LOCATION: MSB 1147, Colloquium Room. Refreshments at 3:30pm in MSB 4110
SPEAKER: Jingchen Liu, Columbia University
TITLE: “A Fused Latent and Graphical Model”
ABSTRACT: One of the main tasks of statistical models is to characterize the dependence structures of multi-dimensional distributions. Latent variable model takes advantage of the fact that the dependence of a high dimensional random vector is often induced by just a few latent (unobserved) factors. Such models are employed in the analysis of marketing, e-commerce, social network, and many other fields where human behaviors are observed and are summarized to a few characteristics. In this talk, we present three real data examples in psychology, finance, and political sciences. In these examples, a common problem is that the dimension grows higher and the dependence structure becomes more complicated. It is hardly possible to find a low dimensional parametric latent variable model that fits well. We enrich the model by including a graphical structure on top of the latent structure. The graph captures the remaining dependence and is often more interpretable than graphs built on marginal dependence.