Approximate Selective Inference via Maximum Likelihood
Author:
Affiliation:
1. Department of Statistics, University of Michigan, Ann Arbor, MI
2. Department of Statistics, Stanford University, Stanford, CA
Funder
NSF
ARO
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/01621459.2022.2081575
Reference30 articles.
1. False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters
2. Valid post-selection inference
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4. SLOPE—Adaptive variable selection via convex optimization
5. A note on data-splitting for the evaluation of significance levels
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