On robust estimation of multiple change points in multivariate and matrix processes

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dc.contributor Cochran, James J.
dc.contributor Barrett, Bruce E.
dc.contributor Davis, Cali M.
dc.contributor Beznosova, Oleksandra
dc.contributor.advisor Perry, Marcus B.
dc.contributor.author Melnykov, Yana
dc.date.accessioned 2018-06-04T14:58:11Z
dc.date.available 2018-06-04T14:58:11Z
dc.date.issued 2017
dc.identifier.other u0015_0000001_0002897
dc.identifier.other Melnykov_alatus_0004D_13352
dc.identifier.uri http://ir.ua.edu/handle/123456789/3573
dc.description Electronic Thesis or Dissertation
dc.description.abstract There are numerous areas of human activities where various processes are observed over time. If the conditions of the process change, it can be reflected through the shift in observed response values. The detection and estimation of such shifts is commonly known as change point inference. While the estimation helps us learn about the process nature, assess its parameters, and analyze identified change points, the detection focuses on finding shifts in the real-time process flow. There is a vast variety of methods proposed in the literature to target change point detections in both settings. Unfortunately, the majority of procedures impose very restrictive assumptions. Some of them include the normality of data, independence of observations, or independence of subjects in multisubject studies. In this dissertation, a new methodology, relying on more realistic assumptions, is developed. This dissertation report includes three chapters. The summary of each chapter is provided below. In the first chapter, we develop methodology capable of estimating and detecting multiple change points in a multisubject single variable process observed over time. In the second chapter, we introduce methodology for the robust estimation of change points in multivariate processes observed over time. In the third chapter, we generalize the ideas presented in the first two chapters by developing methodology capable of identifying multiple change points in multisubject matrix processes observed over time.
dc.format.extent 71 p.
dc.format.medium electronic
dc.format.mimetype application/pdf
dc.language English
dc.language.iso en_US
dc.publisher University of Alabama Libraries
dc.relation.ispartof The University of Alabama Electronic Theses and Dissertations
dc.relation.ispartof The University of Alabama Libraries Digital Collections
dc.relation.hasversion born digital
dc.rights All rights reserved by the author unless otherwise indicated.
dc.subject.other Statistics
dc.title On robust estimation of multiple change points in multivariate and matrix processes
dc.type thesis
dc.type text
etdms.degree.department University of Alabama. Dept. of Information Systems, Statistics, and Management Science
etdms.degree.discipline Applied Statistics
etdms.degree.grantor The University of Alabama
etdms.degree.level doctoral
etdms.degree.name Ph.D.


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