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December 2017 Empirical Bayesian analysis of simultaneous changepoints in multiple data sequences
Zhou Fan, Lester Mackey
Ann. Appl. Stat. 11(4): 2200-2221 (December 2017). DOI: 10.1214/17-AOAS1075

Abstract

Copy number variations in cancer cells and volatility fluctuations in stock prices are commonly manifested as changepoints occurring at the same positions across related data sequences. We introduce a Bayesian modeling framework, BASIC, that employs a changepoint prior to capture the co-occurrence tendency in data of this type. We design efficient algorithms to sample from and maximize over the BASIC changepoint posterior and develop a Monte Carlo expectation-maximization procedure to select prior hyperparameters in an empirical Bayes fashion. We use the resulting BASIC framework to analyze DNA copy number variations in the NCI-60 cancer cell lines and to identify important events that affected the price volatility of S&P 500 stocks from 2000 to 2009.

Citation

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Zhou Fan. Lester Mackey. "Empirical Bayesian analysis of simultaneous changepoints in multiple data sequences." Ann. Appl. Stat. 11 (4) 2200 - 2221, December 2017. https://doi.org/10.1214/17-AOAS1075

Information

Received: 1 July 2016; Revised: 1 April 2017; Published: December 2017
First available in Project Euclid: 28 December 2017

zbMATH: 1383.62205
MathSciNet: MR3743294
Digital Object Identifier: 10.1214/17-AOAS1075

Rights: Copyright © 2017 Institute of Mathematical Statistics

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Vol.11 • No. 4 • December 2017
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