Joint Random Partition Models for Multivariate Change Point Analysis
Conference
64th ISI World Statistics Congress - Ottawa, Canada
Format: IPS Abstract
Keywords: "bayesian, changepoints, financial crisis, time series
Session: IPS 92 - Innovative Nonregular Approaches to Statistical Modelling for Complex Data
Tuesday 18 July 2 p.m. - 3:40 p.m. (Canada/Eastern)
Abstract
Change point analyses identify positions of an ordered stochastic process that undergo abrupt local changes of some underlying distribution. When multiple processes are observed, information regarding the change point positions is often shared across the different processes. This work describes a method that takes advantage of this type of information. Since the number and position of change points can be described through a partition with contiguous clusters, our approach develops a joint model for these types of partitions. We describe computational strategies associated with our approach and illustrate improved performance in detecting change points through a small simulation study. We then apply our method to a financial data set of emerging markets in Latin America and highlight interesting insights discovered due to the correlation between change point locations among these economies.