Abstract
consider hypotheses testing problems for three parameters in high-dimensional linear models with minimal sparsity assumptions of their type but without any compatibility conditions. Under this framework, we construct the first vn-consistent estimators for low-dimensional coefficients, the signal strength, and the noise level. We support our results using numerical simulations and provide comparisons with other estimators.
Original language | English |
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Pages (from-to) | 1467-1495 |
Number of pages | 29 |
Journal | Bernoulli |
Volume | 27 |
Issue number | 3 |
DOIs | |
State | Published - Aug 2021 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2021 International Statistical Institute. All rights reserved.
Keywords
- Compatibility Condition
- Exponential Weighting
- Inference
- Lasso