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2019 Posterior asymptotic normality for an individual coordinate in high-dimensional linear regression
Dana Yang
Electron. J. Statist. 13(2): 3082-3094 (2019). DOI: 10.1214/19-EJS1605

Abstract

It is well known that high-dimensional procedures like the LASSO provide biased estimators of parameters in a linear model. In a 2014 paper Zhang and Zhang showed how to remove this bias by means of a two-step procedure. We show that de-biasing can also be achieved by a one-step estimator, the form of which inspires the development of a Bayesian analogue of the frequentists’ de-biasing techniques.

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Dana Yang. "Posterior asymptotic normality for an individual coordinate in high-dimensional linear regression." Electron. J. Statist. 13 (2) 3082 - 3094, 2019. https://doi.org/10.1214/19-EJS1605

Information

Received: 1 January 2019; Published: 2019
First available in Project Euclid: 24 September 2019

zbMATH: 07113712
MathSciNet: MR4010593
Digital Object Identifier: 10.1214/19-EJS1605

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Vol.13 • No. 2 • 2019
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