Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models-Reference-Cited by-同舟云学术

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Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models

Published:2017-03-13 Issue:2 Volume:35 Page:250-264
ISSN:0735-0015
Container-title:Journal of Business & Economic Statistics
language:en
Short-container-title:Journal of Business & Economic Statistics

Author:

Callot Laurent¹,Caner Mehmet²,Kock Anders Bredahl³,Riquelme Juan Andres⁴

Affiliation:

1. Department of Econometrics and Operations Research, VU University Amsterdam, CREATES, and the Tinbergen Institute, Amsterdam, The Netherlands()

2. Department of Economics, Translational Data Analytics, Department of Statistics, 452 Arps Hall, Ohio State University, Columbus, OH 43210 ()

3. Department of Economics and Business, Aarhus University, Aarhus, Denmark, and CREATES ()

4. Department of Economics,, University of Talca, Chile()

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/07350015.2015.1052461

Reference35 articles.

1. Time-Varying Betas Help in Asset Pricing: The Threshold CAPM

2. Are Real Exchange Rates Nonlinear or Nonstationary? Evidence from a New Threshold Unit Root Test

3. Debt and growth: New evidence for the euro area

4. Simultaneous analysis of Lasso and Dantzig selector

5. Statistics for High-Dimensional Data

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1. Variable selection in threshold model with a covariate-dependent threshold;Empirical Economics;2022-11-30

2. High dimensional threshold model with a time-varying threshold based on Fourier approximation;Studies in Nonlinear Dynamics & Econometrics;2022-05-30

3. Targeting Predictors Via Partial Distance Correlation With Applications to Financial Forecasting;Journal of Business & Economic Statistics;2021-04-22

4. Robust Variable Selection and Estimation in Threshold Regression Model;Acta Mathematicae Applicatae Sinica, English Series;2020-03

5. Oracle Estimation of a Change Point in High-Dimensional Quantile Regression;Journal of the American Statistical Association;2018-06-08

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