Splitting strategies for post-selection inference

Summary We consider the problem of providing valid inference for a selected parameter in a sparse regression setting. It is well known that classical regression tools can be unreliable in this context because of the bias generated in the selection step. Many approaches have been proposed in recent y...

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Bibliographic Details

Published in:	Biometrika Vol. 110; no. 3; pp. 597 - 614
Main Authors:	Rasines, D García, Young, G A
Format:	Journal Article
Language:	English
Published:	Oxford University Press 01.09.2023
Subjects:	Regression Randomization Data splitting Post-selection inference Variable selection
ISSN:	0006-3444, 1464-3510
Online Access:	Get full text
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