Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Vo, Thi Phuong Thuy"'
We study the exploration of an Erd\"os-R\'enyi random graph by a respondent-driven sampling method, where discovered vertices reveal their neighbours. Some of them receive coupons to reveal in their turn their own neighbourhood. This leads to the stu
Externí odkaz:
http://arxiv.org/abs/2103.16306
Autor:
Tran, Viet Chi, Vo, Thi Phuong Thuy
We are interested in recovering information on a stochastic block model from the subgraph discovered by an exploring random walk. Stochastic block models correspond to populations structured into a finite number of types, where two individuals are co
Externí odkaz:
http://arxiv.org/abs/2006.08010
Autor:
Vo, Thi Phuong Thuy
The discovery of the "hidden population", whose size and membership are unknown, is made possible by assuming that its members are connected in a social network by their relationships. We explore these groups by a chain-referral sampling (CRS) method
Externí odkaz:
http://arxiv.org/abs/1902.04990
Publikováno v:
Journal of Urban Archaeology. 7:51-76
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a87855528cb0a51ffb3c7f852c01266a
https://doi.org/10.1484/j.jua.5.133450
https://doi.org/10.1484/j.jua.5.133450
Publikováno v:
Acta Mathematica Vietnamica; Sep2023, Vol. 48 Issue 3, p479-513, 35p
Publikováno v:
World Archaeology. 53:345-368
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b28ea666a8758dd59a45338f901c4c51
https://doi.org/10.1080/00438243.2021.2002717
https://doi.org/10.1080/00438243.2021.2002717
Autor:
Vo, Thi Phuong Thuy
Publikováno v:
Mathematics [math]. Université Sorbonne Paris Nord, 2020. English
The study of Respondent Driven Sampling (RDS) is invested for the discovery of a social network of hidden populations. It leads to the study of a Markov chain on a random graph whose vertices represent individuals and whose edges describe the relatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______212::438380a54a9038b242bf26a1146f2f34
https://tel.archives-ouvertes.fr/tel-03104255/file/main.pdf
https://tel.archives-ouvertes.fr/tel-03104255/file/main.pdf
Autor:
Vo, Thi Phuong Thuy
Publikováno v:
Géométrie algébrique [math.AG]. Université Paris-Nord-Paris XIII, 2020. Français. ⟨NNT : 2020PA131024⟩
The study of Respondent Driven Sampling (RDS) is invested for the discovery ofa social network of hidden populations. It leads to the study of a Markov chainon a random graph whose vertices represent individuals and whose edges describethe relationsh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::fdc79dd67739375ed94352507c735c5d
https://tel.archives-ouvertes.fr/tel-03355967/document
https://tel.archives-ouvertes.fr/tel-03355967/document
Autor:
Vo, Thi Phuong Thuy
Publikováno v:
Mathematics [math]. Université Sorbonne Paris Nord, 2020. English
The study of Respondent Driven Sampling (RDS) is invested for the discovery of a social network of hidden populations. It leads to the study of a Markov chain on a random graph whose vertices represent individuals and whose edges describe the relatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2592::438380a54a9038b242bf26a1146f2f34
https://tel.archives-ouvertes.fr/tel-03104255/file/main.pdf
https://tel.archives-ouvertes.fr/tel-03104255/file/main.pdf
Autor:
Tran, Viet-Chi, Vo Thi Phuong, Thuy
Publikováno v:
Electronic Journal of Statistics
Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2021, 15 (2), pp.5855-5887. ⟨10.1214/21-EJS1899⟩
Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2021, 15 (2), pp.5855-5887. ⟨10.1214/21-EJS1899⟩
International audience; We are interested in recovering information on a stochastic block model from the subgraph discovered by an exploring random walk. Stochastic block models correspond to populations structured into a finite number of types, wher
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dab56bf113780fdcf3a5638ed3fcdaa
https://hal.archives-ouvertes.fr/hal-02867642/file/estimationSBM-HALarXiv14062020.pdf
https://hal.archives-ouvertes.fr/hal-02867642/file/estimationSBM-HALarXiv14062020.pdf