Lasso for sparse linear regression with exponentially β-mixing errors

Fang Xie, Lihu Xu and Youcai Yang

Statistics & Probability Letters, 2017, vol. 125, issue C, 64-70

Abstract: We prove two consistency theorems for the lasso estimators of sparse linear regression models with exponentiallyβ-mixing errors, in which the number of regressors p is large, even much larger than the sample size n.

Keywords: Lasso; Linear regression models; Consistency; Exponentiallyβ-mixing errors (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2017.01.023

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