Exact selective inference with randomization
成果类型：
Article
署名作者：
Panigrahi, Snigdha; Fry, Kevin; Taylor, Jonathan
署名单位：
University of Michigan System; University of Michigan; Stanford University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asae019
发表日期：
2024
关键词：
摘要：
We introduce a pivot for exact selective inference with randomization. Not only does our pivot lead to exact inference in Gaussian regression models, but it is also available in closed form. We reduce this problem to inference for a bivariate truncated Gaussian variable. By doing so, we give up some power that is achieved with approximate maximum likelihood estimation in . Yet our pivot always produces narrower confidence intervals than a closely related data-splitting procedure. We investigate the trade-off between power and exact selective inference on simulated datasets and an HIV drug resistance dataset.