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Detection of multiple change-points ...

Zhang, Wei.

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Detection of multiple change-points in hazard models.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Detection of multiple change-points in hazard models./
作者:	Zhang, Wei.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2014,
面頁冊數:	82 p.
附註:	Source: Dissertations Abstracts International, Volume: 76-01, Section: B.
Contained By:	Dissertations Abstracts International76-01B.
標題:	Statistics. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3584937
ISBN:	9781303979132

Detection of multiple change-points in hazard models.
Zhang, Wei.

Detection of multiple change-points in hazard models. - Ann Arbor : ProQuest Dissertations & Theses, 2014 - 82 p.

Source: Dissertations Abstracts International, Volume: 76-01, Section: B.

Thesis (Ph.D.)--Florida Atlantic University, 2014.

.

Change-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step further, we propose an counting process based and least squares based change-point detection algorithm. For single change-point case, consistency results are obtained. We then consider the detection of multiple change-points in the presence of long-term survivors via maximum likelihood based and counting process based method. Last but not least, we use a weighted least squares based and counting process based method for detection of multiple change-points with long-term survivors and covariates. For multiple change-points detection, simulation studies show good performances of our estimators under various parameters settings for both methods. All methods are applied to real data analyses.

ISBN: 9781303979132Subjects--Topical Terms:

517247
Statistics.
Subjects--Index Terms:

Change-point detection

Detection of multiple change-points in hazard models.
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245 1 0 $a Detection of multiple change-points in hazard models.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2014
300 $a 82 p.
500 $a Source: Dissertations Abstracts International, Volume: 76-01, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Qian, Lianfen.
502 $a Thesis (Ph.D.)--Florida Atlantic University, 2014.
506 $a .
520 $a Change-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step further, we propose an counting process based and least squares based change-point detection algorithm. For single change-point case, consistency results are obtained. We then consider the detection of multiple change-points in the presence of long-term survivors via maximum likelihood based and counting process based method. Last but not least, we use a weighted least squares based and counting process based method for detection of multiple change-points with long-term survivors and covariates. For multiple change-points detection, simulation studies show good performances of our estimators under various parameters settings for both methods. All methods are applied to real data analyses.
590 $a School code: 0119.
650 4 $a Statistics. $3 517247
650 4 $a Applied mathematics. $3 2122814
653 $a Change-point detection
653 $a Consistency results
653 $a Hazard rate
653 $a Parameter estimation
653 $a Survival analysis
690 $a 0364
690 $a 0463
710 2 $a Florida Atlantic University. $b Mathematical Sciences. $3 2094770
773 0 $t Dissertations Abstracts International $g 76-01B.
790 $a 0119
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3584937