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Selective inference in regression models with groups of variables

arXiv 1511.01478 ↗First posted 4 Nov 2015stat.ME math.ST stat.THcited by 9

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Abstract (arXiv)

We provide a general mathematical framework for selective inference with supervised model selection procedures characterized by quadratic forms in the outcome variable. Forward stepwise with groups of variables is an important special case as it allows models with categorical variables or factors. Models can be chosen by AIC, BIC, or a fixed number of steps. We provide an exact significance test for each group of variables in the selected model based on an appropriately truncated chi or F distribution for the cases of known and unknown σ2 respectively. An efficient software implementation is available as a package in the R statistical programming language.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Nov 2015.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 0; 2024: 0; 2025: 1.

9 papers.