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pro vyhledávání: '"Rothman, Adam"'
We propose new methods for multivariate linear regression when the regression coefficient matrix is sparse and the error covariance matrix is dense. We assume that the error covariance matrix has equicorrelation across the response variables. Two pro
Externí odkaz:
http://arxiv.org/abs/2410.10025
Modeling the complex relationships between multiple categorical response variables as a function of predictors is a fundamental task in the analysis of categorical data. However, existing methods can be difficult to interpret and may lack flexibility
Externí odkaz:
http://arxiv.org/abs/2410.04356
A hierarchical Bayesian approach that permits simultaneous inference for the regression coefficient matrix and the error precision (inverse covariance) matrix in the multivariate linear model is proposed. Assuming a natural ordering of the elements o
Externí odkaz:
http://arxiv.org/abs/2406.00906
Autor:
Ham, Daeyoung, Rothman, Adam J.
We propose a penalized least-squares method to fit the linear regression model with fitted values that are invariant to invertible linear transformations of the design matrix. This invariance is important, for example, when practitioners have categor
Externí odkaz:
http://arxiv.org/abs/2307.03317
Autor:
Rothman, Adam L., Gibbons, Allister
Publikováno v:
In American Journal of Ophthalmology September 2024 265:88-96
Publikováno v:
Scientific Reports. 8/16/2024, Vol. 14 Issue 1, p1-11. 11p.
Publikováno v:
In Ophthalmology July 2024 131(7):780-789
Autor:
Rothman, Adam L., Beca, Flavius A., Tijerina, Jonathan D., Schuman, Darren M., Parrish, Richard K., II, Vanner, Elizabeth A., Liu, Katy C.
Publikováno v:
In Ophthalmology Glaucoma May-June 2024 7(3):260-270