Understanding Variability Between Groups of Sequences Using a Bayesian Object-Oriented Data Model

• Activity Number: 686
• Type: Contributed
• Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Maria Tackett* and Dan Spitzner
• Companies: University of Virginia and University of Virginia
• Keywords: Bayesian Methods ; Life course data ; object-oriented data ; Optimal Matching ; Sequence analysis ; Social Sciences

Abstract

Optimal Matching is an algorithm used to analyze object-oriented data, specifically sequences. In this article, we propose a framework inspired by classical Analysis of Variance to estimate the variability between groups of sequences using Optimal Matching. To estimate between group vari- ability, we explore approaches based on established methods- bootstrapping and Hidden Markov Models. We also propose a Bayesian object-oriented model. These three methods are examined and demonstrated on a well-known dataset of historical English dance sequences, with a mind towards application to life course data.