5 citations · 9 across the 5 of their papers we have counts for
6 papers
On Efficient Design of Pilot Experiment for Generalized Linear Models
Yiou Li, Xinwei Deng
The experimental design for a generalized linear model (GLM) is important but challenging since the design criterion often depends on model specification including the link functio…
A Maximin -Efficient Design for Multivariate GLM
Yiou Li, Lulu Kang, Xinwei Deng
Experimental designs for a generalized linear model (GLM) often depend on the specification of the model, including the link function, the predictors, and unknown parameters, such…
Covariate Balancing Based on Kernel Density Estimates for Controlled Experiments
Yiou Li, Lulu Kang, Xiao Huang
Controlled experiments are widely used in many applications to investigate the causal relationship between input factors and experimental outcomes. A completely randomized design i…
Is a Transformed Low Discrepancy Design Also Low Discrepancy?
Yiou Li, Lulu Kang, Fred J. Hickernell
Experimental designs intended to match arbitrary target distributions are typically constructed via a variable transformation of a uniform experimental design. The inverse distribu…
Kernel Discrepancy-Based Rerandomization for Controlled Experiments
Yiou Li, Lulu Kang
This paper introduces a kernel discrepancy-based framework for rerandomization to enhance the precision of causal inference in controlled experiments. We demonstrate that the kerne…
An Efficient Algorithm for Elastic I-optimal Design of Generalized Linear Models
Yiou Li, Xinwei Deng
The generalized linear models (GLMs) are widely used in statistical analysis and the related design issues are undoubtedly challenging. The state-of-the-art works mostly apply to d…