Parametric statistical change point analysis: With applications to genetics, medicine, and finance

Jie Chen, Arjun K. Gupta

Research output: Book/ReportBook

18 Citations (Scopus)

Abstract

This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data. The exposition throughout the work is clear and systematic, with a great deal of introductory material included. Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature. Extensive examples throughout the text emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as the Bayesian and information criterion approaches. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control are added in this second edition. Also included are two new chapters on change points in the hazard function and other practical change point models such as the epidemic change point model and a smooth-and-abrupt change point model. An up-to-date comprehensive bibliography and two indices round out the work.

Original languageEnglish (US)
PublisherBirkhauser Boston
Number of pages273
ISBN (Electronic)9780817648015
ISBN (Print)0817648003, 9780817648008
DOIs
StatePublished - Jan 1 2014

Fingerprint

Change-point Analysis
Change-point Model
Finance
Medicine
Change-point Problem
Statistical Analysis
Likelihood Ratio Criterion
Biomedical Imaging
Air Traffic Control
Geology
Comparative Genomics
Information Criterion
Exponential Model
Hazard Function
Molecular Biology
Change Point
Epidemic Model
Gene Expression Data
Statistical Model
Signal Processing

ASJC Scopus subject areas

  • Mathematics(all)

Cite this

Parametric statistical change point analysis : With applications to genetics, medicine, and finance. / Chen, Jie; Gupta, Arjun K.

Birkhauser Boston, 2014. 273 p.

Research output: Book/ReportBook

@book{214186a9fb02460f80f074e7eb1fa184,
title = "Parametric statistical change point analysis: With applications to genetics, medicine, and finance",
abstract = "This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data. The exposition throughout the work is clear and systematic, with a great deal of introductory material included. Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature. Extensive examples throughout the text emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as the Bayesian and information criterion approaches. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control are added in this second edition. Also included are two new chapters on change points in the hazard function and other practical change point models such as the epidemic change point model and a smooth-and-abrupt change point model. An up-to-date comprehensive bibliography and two indices round out the work.",
author = "Jie Chen and Gupta, {Arjun K.}",
year = "2014",
month = "1",
day = "1",
doi = "10.1007/978-0-8176-4801-5",
language = "English (US)",
isbn = "0817648003",
publisher = "Birkhauser Boston",

}

TY - BOOK

T1 - Parametric statistical change point analysis

T2 - With applications to genetics, medicine, and finance

AU - Chen, Jie

AU - Gupta, Arjun K.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data. The exposition throughout the work is clear and systematic, with a great deal of introductory material included. Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature. Extensive examples throughout the text emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as the Bayesian and information criterion approaches. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control are added in this second edition. Also included are two new chapters on change points in the hazard function and other practical change point models such as the epidemic change point model and a smooth-and-abrupt change point model. An up-to-date comprehensive bibliography and two indices round out the work.

AB - This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data. The exposition throughout the work is clear and systematic, with a great deal of introductory material included. Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature. Extensive examples throughout the text emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as the Bayesian and information criterion approaches. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control are added in this second edition. Also included are two new chapters on change points in the hazard function and other practical change point models such as the epidemic change point model and a smooth-and-abrupt change point model. An up-to-date comprehensive bibliography and two indices round out the work.

UR - http://www.scopus.com/inward/record.url?scp=84926430989&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84926430989&partnerID=8YFLogxK

U2 - 10.1007/978-0-8176-4801-5

DO - 10.1007/978-0-8176-4801-5

M3 - Book

AN - SCOPUS:84926430989

SN - 0817648003

SN - 9780817648008

BT - Parametric statistical change point analysis

PB - Birkhauser Boston

ER -