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Hierarchical testing of variable importance

Abstract:

A frequently encountered challenge in high-dimensional regression is the detection of relevant variables. Variable selection suffers from instability and the power to detect relevant variables is typically low if predictor variables are highly correlated. When taking the multiplicity of the testing problem into account, the power diminishes even further. To gain power and insight, it can be advantageous to look for influence not at the level of individual variables but rather at the level of ...

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Publication status:
Published

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Publisher copy:
10.1093/biomet/asn007

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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Role:
Author
Journal:
BIOMETRIKA
Volume:
95
Issue:
2
Pages:
265-278
Publication date:
2008-06-05
DOI:
EISSN:
1464-3510
ISSN:
0006-3444
URN:
uuid:b3bb4e46-4db2-4c9d-afc1-52b99104d988
Source identifiers:
97749
Local pid:
pubs:97749

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