Zobrazeno 1 - 10
of 1 204
pro vyhledávání: '"penalized-likelihood methods"'
Autor:
Bui, Minh Thu1 (AUTHOR), Potgieter, Cornelis J.1,2 (AUTHOR) c.potgieter@tcu.edu, Kamata, Akihito3 (AUTHOR)
Publikováno v:
Journal of Applied Statistics. Dec2023, Vol. 50 Issue 15, p3157-3176. 20p.
The paper considers parameter estimation in count data models using penalized likelihood methods. The motivating data consists of multiple independent count variables with a moderate sample size per variable. The data were collected during the assess
Externí odkaz:
http://arxiv.org/abs/2109.14010
Akademický článek
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Autor:
Shojaie, Ali, Michailidis, George
Directed acyclic graphs (DAGs) are commonly used to represent causal relationships among random variables in graphical models. Applications of these models arise in the study of physical, as well as biological systems, where directed edges between no
Externí odkaz:
http://arxiv.org/abs/0911.5439
Autor:
SHOJAIE, ALI, MICHAILIDIS, GEORGE
Publikováno v:
Biometrika, 2010 Sep 01. 97(3), 519-538.
Externí odkaz:
https://www.jstor.org/stable/25734106
Autor:
Gijbels, I., Klonias, V. K.
Publikováno v:
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1991 Mar 01. 19(1), 23-38.
Externí odkaz:
https://www.jstor.org/stable/3315534
Autor:
Bui MT; Department of Mathematics, Texas Christian University, Fort Worth, TX, USA., Potgieter CJ; Department of Mathematics, Texas Christian University, Fort Worth, TX, USA.; Department of Statistics, University of Johannesburg, Johannesburg, South Africa., Kamata A; Simmons School of Education, Southern Methodist University, Dallas, TX, USA.
Publikováno v:
Journal of applied statistics [J Appl Stat] 2022 Jul 22; Vol. 50 (15), pp. 3157-3176. Date of Electronic Publication: 2022 Jul 22 (Print Publication: 2023).
The paper considers parameter estimation in count data models using penalized likelihood methods. The motivating data consists of multiple independent count variables with a moderate sample size per variable. The data were collected during the assess
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28568f151464729e54a51b227f8cb769
http://arxiv.org/abs/2109.14010
http://arxiv.org/abs/2109.14010
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Xue Ren, Soo-Jin Lee
Publikováno v:
IEEE Access, Vol 12, Pp 182590-182602 (2024)
This paper presents example-based methods for super-resolution (SR) reconstruction from a single set of low-resolution projections (or a sinogram) in positron emission tomography (PET). While deep learning-based SR approaches have shown promise acros
Externí odkaz:
https://doaj.org/article/7c96c1cd5d7e49bfaeb42a518f68ef3a