Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Ren, Yangfan"'
Publikováno v:
Biometrics (2024)
In this paper, we propose Varying Effects Regression with Graph Estimation (VERGE), a novel Bayesian method for feature selection in regression. Our model has key aspects that allow it to leverage the complex structure of data sets arising from genom
Externí odkaz:
http://arxiv.org/abs/2407.05089
Autor:
Ren, Yangfan, Osborne, Nathan, Peterson, Christine B., DeMaster, Dana M., Ewing-Cobbs, Linda, Vannucci, Marina
Publikováno v:
Human Brain Mapping (2024), 45(10), e26763
In this paper, we develop an analytical approach for estimating brain connectivity networks that accounts for subject heterogeneity. More specifically, we consider a novel extension of a multi-subject Bayesian vector autoregressive model that estimat
Externí odkaz:
http://arxiv.org/abs/2405.00535
Autor:
Ren Y; Department of Statistics, Rice University, Houston, TX 77005, United States., Peterson CB; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States., Vannucci M; Department of Statistics, Rice University, Houston, TX 77005, United States.
Publikováno v:
Biometrics [Biometrics] 2024 Oct 03; Vol. 80 (4).
Autor:
Ren Y; Department of Statistics, Rice University, Houston, Texas, USA., Osborne N; Intuit, San Diego, California, USA., Peterson CB; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA., DeMaster DM; Department of Pediatrics, Children's Learning Institute, University of Texas Health Science Center, Houston, Texas, USA., Ewing-Cobbs L; Department of Pediatrics, Children's Learning Institute, University of Texas Health Science Center, Houston, Texas, USA., Vannucci M; Department of Statistics, Rice University, Houston, Texas, USA.
Publikováno v:
Human brain mapping [Hum Brain Mapp] 2024 Jul 15; Vol. 45 (10), pp. e26763.