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020 ▼a 9780438291379
035 ▼a (MiAaPQ)AAI10826454
035 ▼a (MiAaPQ)ucdavis:17983
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 510
1001 ▼a Sonmez, Ozan.
24510 ▼a Structural Breaks in Functional Time Series Data.
260 ▼a [S.l.] : ▼b University of California, Davis., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 150 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Adviser: Alexander Aue.
5021 ▼a Thesis (Ph.D.)--University of California, Davis, 2018.
520 ▼a Structural break analysis in functional data is explored. First, methodology is proposed to uncover structural breaks in the mean function of functional data that is "fully functional" in the sense that it does not rely on dimension reduction te
520 ▼a Second, we establish the weak convergence of the process of partial sample estimates of the eigenvalues and eigenfunctions, or principal components, defined by the covariance operator of stationary functional time series. Based on the asymptotic
520 ▼a Finally, we discuss an R package, fChange, for structural break analysis in functional data that implements the proposed methods. This package aims to provide practical implementations that can be used by interested practitioners.
590 ▼a School code: 0029.
650 4 ▼a Mathematics.
650 4 ▼a Computer science.
690 ▼a 0405
690 ▼a 0984
71020 ▼a University of California, Davis. ▼b Statistics.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0029
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998890 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자