5 citations · 6 across the 4 of their papers we have counts for
4 papers
Statistical thinking in simulation design: a continuing conversation on the balancing intercept problem
Boyi Guo, Linzi Li, Jacqueline E. Rudolph
Epidemiologists have a growing interest in employing computational approaches to solve analytic problems, with simulation being arguably the most accessible among all approaches. W…
The R Package BHAM: Fast and Scalable Bayesian Hierarchical Additive Model for High-dimensional Data
Boyi Guo, Nengjun Yi
BHAM is a freely avaible R pakcage that implments Bayesian hierarchical additive models for high-dimensional clinical and genomic data. The package includes functions that generali…
A scalable and flexible Cox proportional hazards model for high-dimensional survival prediction and functional selection
Boyi Guo, Nengjun Yi
Cox proportional hazards model is one of the most popular models in biomedical data analysis. There have been continuing efforts to improve the flexibility of such models for compl…
Spike-and-Slab LASSO Generalized Additive Models and Scalable Algorithms for High-Dimensional Data Analysis
Boyi Guo, Byron C. Jaeger, A. K. M. Fazlur Rahman +2
There are proposals that extend the classical generalized additive models (GAMs) to accommodate high-dimensional data () using group sparse regularization. However, the spars…