Square†Root LASSO for High†Dimensional Sparse Linear Systems with Weakly Dependent Errors

Fang Xie and Zhijie Xiao

Journal of Time Series Analysis, 2018, vol. 39, issue 2, 212-238

Abstract: We study the square†root LASSO method for high†dimensional sparse linear models with weakly dependent errors. The asymptotic and non†asymptotic bounds for the estimation errors are derived. Our results cover a wide range of weakly dependent errors, including α†mixing, Ï â€ mixing, ϕ†mixing, and m†dependent types. Numerical simulations are conducted to show the consistency property of square†root LASSO. An empirical application to financial data highlights the importance of the results and method.

Date: 2018
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