arXiv Open Access 2019

Inference Without Compatibility

Michael Law Ya'acov Ritov

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Abstrak

We 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 $\sqrt{n}$-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.

Topik & Kata Kunci

math.ST

Penulis (2)

Michael Law

Ya'acov Ritov

Format Sitasi

APA MLA BibTeX

Law, M., Ritov, Y. (2019). Inference Without Compatibility. https://arxiv.org/abs/1903.06295

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Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓