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Topological Statistics - Weak Signals and Inhomogeneous Models
Topological Statistics - Weak Signals and Inhomogeneous Models
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211152137
- ISBN
- 9798384050964
- DDC
- 519
- 저자명
- Siu, Chun Yin.
- 서명/저자
- Topological Statistics - Weak Signals and Inhomogeneous Models
- 발행사항
- [Sl] : Cornell University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 257 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
- 주기사항
- Advisor: Samorodnitsky, Gennady.
- 학위논문주기
- Thesis (Ph.D.)--Cornell University, 2024.
- 초록/해제
- 요약Topological data analysis (TDA) is an emerging branch of data science that utilizes algebraic topology. Despite its wide range of applications, it has been challenging to apply statistical principles to the study of topological properties of datasets. In this thesis, we push the frontiers of statistical topology by developing a method to identify small topological features, and studying the topological properties of preferential attachment graphs, a class of inhomogeneous random graph models.
- 일반주제명
- Applied mathematics
- 일반주제명
- Mathematics
- 일반주제명
- Statistics
- 키워드
- Scale invariance
- 기타저자
- Cornell University Applied Mathematics
- 기본자료저록
- Dissertations Abstracts International. 86-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798384050964
■035 ▼a(MiAaPQ)AAI31484328
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a519
■1001 ▼aSiu, Chun Yin.▼0(orcid)0000-0001-9157-2618
■24510▼aTopological Statistics - Weak Signals and Inhomogeneous Models
■260 ▼a[Sl]▼bCornell University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a257 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-03, Section: B.
■500 ▼aAdvisor: Samorodnitsky, Gennady.
■5021 ▼aThesis (Ph.D.)--Cornell University, 2024.
■520 ▼aTopological data analysis (TDA) is an emerging branch of data science that utilizes algebraic topology. Despite its wide range of applications, it has been challenging to apply statistical principles to the study of topological properties of datasets. In this thesis, we push the frontiers of statistical topology by developing a method to identify small topological features, and studying the topological properties of preferential attachment graphs, a class of inhomogeneous random graph models.
■590 ▼aSchool code: 0058.
■650 4▼aApplied mathematics
■650 4▼aMathematics
■650 4▼aStatistics
■653 ▼aRandom simplicial complexes
■653 ▼aScale invariance
■653 ▼aScale-free network
■653 ▼aTopological data analysis
■653 ▼aTopological statistics
■653 ▼aWeak topological signals
■690 ▼a0364
■690 ▼a0405
■690 ▼a0463
■71020▼aCornell University▼bApplied Mathematics.
■7730 ▼tDissertations Abstracts International▼g86-03B.
■790 ▼a0058
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163117▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
