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Essays in Applied Bayesian Analysis.
~
Chen, Xinyuan.
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Essays in Applied Bayesian Analysis.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Essays in Applied Bayesian Analysis./
Author:
Chen, Xinyuan.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:
209 p.
Notes:
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Contained By:
Dissertations Abstracts International83-02B.
Subject:
Statistics. -
Online resource:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28322109
ISBN:
9798522999162
Essays in Applied Bayesian Analysis.
Chen, Xinyuan.
Essays in Applied Bayesian Analysis.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 209 p.
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Thesis (Ph.D.)--Yale University, 2021.
This item must not be sold to any third party vendors.
With continuing rapid developments in computational power, Bayesian statistical methods, because of their user-friendliness and estimation capabilities, have become increasingly popular in a considerable variety of application fields. In this thesis, applied Bayesian methodological topics and empirical examples focusing on nonhomogeneous hidden Markov models (NHMMs) and measurement error models are explored in three chapters. In the first chapter, a subsequence-based variational Bayesian inference framework for NHMMs is proposed in order to address the computational problems encountered when analyzing datasets containing long sequences. The second chapter concentrates on measurement error models, where a Bayesian estimation procedure is proposed for the partial potential impact fraction (pPIF) with the presence of measurement error. The third chapter focuses on an empirical application in marketing, where a coupled nonhomogeneous hidden Markov model (CNHMM) is introduced to provide a novel framework for customer relationship management.
ISBN: 9798522999162Subjects--Topical Terms:
517247
Statistics.
Subjects--Index Terms:
Applied Bayesian analysis
Essays in Applied Bayesian Analysis.
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With continuing rapid developments in computational power, Bayesian statistical methods, because of their user-friendliness and estimation capabilities, have become increasingly popular in a considerable variety of application fields. In this thesis, applied Bayesian methodological topics and empirical examples focusing on nonhomogeneous hidden Markov models (NHMMs) and measurement error models are explored in three chapters. In the first chapter, a subsequence-based variational Bayesian inference framework for NHMMs is proposed in order to address the computational problems encountered when analyzing datasets containing long sequences. The second chapter concentrates on measurement error models, where a Bayesian estimation procedure is proposed for the partial potential impact fraction (pPIF) with the presence of measurement error. The third chapter focuses on an empirical application in marketing, where a coupled nonhomogeneous hidden Markov model (CNHMM) is introduced to provide a novel framework for customer relationship management.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28322109
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