Extreme eigenvalues of m-dependent heavy-tailed matrices = 종속성이 있는 두터운 꼬리 랜덤 행렬에서 최대 고유 값들의 분포

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 24
  • Download : 0
We analyze the largest eigenvalue statistics of two standard types of symmetric random matrix models having entry-wise regularly varying tail distributions with parameter 0 < $\alpha$ < 4. Our analysis extends results in the previous literature for symmetric matrices with independent entries above the diagonal, by allowing for m-dependence between the entries of a given matrix. We prove that the limiting point process of extreme eigenvalues is a Poisson cluster process.
Advisors
Jund, Paulresearcher정폴researcher
Description
한국과학기술원 :수리과학과,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 수리과학과, 2019.8,[iii, 35 p. :]

Keywords

heavy-tailed matrices▼apoisson cluster process▼aregular variation▼asample covariance matrices▼arandom matrices; 랜덤 행렬▼a푸아송 다발 과정▼a정칙 변동▼a표본 공분산 행렬

URI
http://hdl.handle.net/10203/283242
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=871409&flag=dissertation
Appears in Collection
MA-Theses_Ph.D.(박사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0