Non-crossing non-parametric estimates of quantile curves H Dette, S Volgushev
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2008
184 2008 Distributed inference for quantile regression processes S Volgushev, SK Chao, G Cheng
154 2019 Empirical and sequential empirical copula processes under serial dependence A Bücher, S Volgushev
Journal of Multivariate Analysis 119, 61-70, 2013
98 2013 Quantile spectral processes: Asymptotic analysis and inference T Kley, S Volgushev, H Dette, M Hallin
92 2016 Of copulas, quantiles, ranks and spectra: An H Dette, M Hallin, T Kley, S Volgushev
88 2015 New estimators of the Pickands dependence function and a test for extreme-value dependence A Bücher, H Dette, S Volgushev
86 2011 Inference for change points in high-dimensional data via selfnormalization R Wang, C Zhu, S Volgushev, X Shao
The Annals of Statistics 50 (2), 781-806, 2022
65 2022 Panel data quantile regression with grouped fixed effects J Gu, S Volgushev
Journal of Econometrics 213 (1), 68-91, 2019
53 2019 A subsampled double bootstrap for massive data S Sengupta, S Volgushev, X Shao
Journal of the American Statistical Association 111 (515), 1222-1232, 2016
53 2016 When uniform weak convergence fails: Empirical processes for dependence functions and residuals via epi-and hypographs A Bücher, J Segers, S Volgushev
52 2014 Equivalence of regression curves H Dette, K Möllenhoff, S Volgushev, F Bretz
Journal of the American Statistical Association 113 (522), 711-729, 2018
50 2018 An analysis of constant step size SGD in the non-convex regime: Asymptotic normality and bias L Yu, K Balasubramanian, S Volgushev, MA Erdogdu
Advances in Neural Information Processing Systems 34, 4234-4248, 2021
49 2021 Quantile spectral analysis for locally stationary time series S Birr, S Volgushev, T Kley, H Dette, M Hallin
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017
48 2017 Testing relevant hypotheses in functional time series via self-normalization H Dette, K Kokot, S Volgushev
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020
47 2020 Some comments on copula-based regression H Dette, R Van Hecke, S Volgushev
Journal of the American Statistical Association 109 (507), 1319-1324, 2014
43 2014 Weak convergence of the empirical copula process with respect to weighted metrics B Berghaus, A Bücher, S Volgushev
42 2017 Structure learning for extremal tree models S Engelke, S Volgushev
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022
41 2022 On the unbiased asymptotic normality of quantile regression with fixed effects AF Galvao, J Gu, S Volgushev
Journal of Econometrics 218 (1), 178-215, 2020
36 2020 A test for Archimedeanity in bivariate copula models A Bücher, H Dette, S Volgushev
Journal of Multivariate Analysis 110, 121-132, 2012
34 2012 Quantile processes for semi and nonparametric regression SK Chao, S Volgushev, G Cheng
Electronic Journal of Statistics 11 (2), 3272-3331, 2017
30 2017 
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