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The lasso for high-dimensional regression with a possible change-point
Lee, Sokbae; Seo, Myung Hwan; Shin, Youngki - 2014
the Lasso estimator of regression coefficients as well as the threshold parameter. Our Lasso estimator not only selects …-asymptotic oracle inequalities for both the prediction risk and the l1 estimation loss for regression coefficients. Since the Lasso …
Persistent link: https://www.econbiz.de/10011282656
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The lasso for high-dimensional regression with a possible change-point
Lee, Sokbae; Seo, Myung Hwan; Shin, Youngki - 2014
the Lasso estimator of regression coefficients as well as the threshold parameter. Our Lasso estimator not only selects …-asymptotic oracle inequalities for both the prediction risk and the l1 estimation loss for regression coefficients. Since the Lasso …
Persistent link: https://www.econbiz.de/10010358938
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Regression discontinuity design with potentially many covariates
Arai, Yoichi; Otsu, Taisuke; Seo, Myung Hwan - 2022
Persistent link: https://www.econbiz.de/10014430086
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Testing stochastic dominance with many conditioning variables
Linton, Oliver; Seo, Myung Hwan; Whang, Yoon-jae - 2020
Persistent link: https://www.econbiz.de/10012793096
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High-dimensional predictive regression in the presence of cointegration
Koo, Bonsoo; Anderson, Heather M.; Seo, Myung Hwan; … - In: Journal of econometrics 219 (2020) 2, pp. 456-477
Persistent link: https://www.econbiz.de/10012483404
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Testing stochastic dominance with many conditioning variables
Linton, Oliver; Seo, Myung Hwan; Whang, Yoon-jae - 2020
Persistent link: https://www.econbiz.de/10014311275