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Structural Breaks in Functional Time Series Data
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Structural Breaks in Functional Time Series Data. |
| 개인저자 | Sonmez, Ozan. |
| 단체저자명 | University of California, Davis. Statistics. |
| 발행사항 | [S.l.]: University of California, Davis., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 150 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438291379 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Davis, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Alexander Aue. |
| 요약 | 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 |
| 요약 | 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 |
| 요약 | 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. |
| 일반주제명 | Mathematics. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
