Some Novel Aspects of Quantile Regression: Local Stationarity, Random Forests, and Optimal Transportation
Manon Felix (),
Davide La Vecchia (),
Hang Liu () and
Yiming Ma ()
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Manon Felix: University of Geneva, Research Center for Statistics and Geneva School of Economics and Management
Davide La Vecchia: University of Geneva, Research Center for Statistics and Geneva School of Economics and Management
Hang Liu: University of Science and Technology of China, Faculty of Business in SciTech, School of Management
Yiming Ma: University of Science and Technology of China, Department of Statistics and Finance, School of Management
A chapter in Recent Advances in Econometrics and Statistics, 2024, pp 261-282 from Springer
Abstract:
Abstract This paper is written for a Festschrift in honor of Professor Marc Hallin, and it proposes some developments on quantile regression. We connect our investigation to Marc’s scientific production, and we present some theoretical and methodological advances for quantile estimation in nonstandard settings. We split our contributions in two parts. The first part is about conditional quantile estimation for nonstationary time series. The second part is about conditional quantile estimation for the analysis of multivariate independent data in the presence of possibly large-dimensional covariates. Monte Carlo studies illustrate numerically the performance of our methods and compare them to some extant techniques.
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-61853-6_14
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DOI: 10.1007/978-3-031-61853-6_14
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