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Bayesian Registration of Real-Valued Functions

Date:
Location:
MDS 220
Speaker(s) / Presenter(s):
Dr. Yi Lu - Drew University

Abstract: In this talk, I will present a Bayesian framework for registration of real-valued functional data.  I will introduce function registration and its statistical setup, as well as a series of transformations, developed under a differential geometric framework, that simply the data and functional parameters.  Approximate draws from the posterior distribution are obtained using a novel Markov chain Monte Carlo (MCMC) algorithm which is well suited for estimation of functions.  Both simulated and real datasets will be presented to illustrate the proposed approach.

 

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