Non‐crossing non‐parametric estimates of quantile curves H Dette, S Volgushev
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2008
164 2008 Distributed inference for quantile regression processes S Volgushev, SK Chao, G Cheng
98 2019 Empirical and sequential empirical copula processes under serial dependence A Bücher, S Volgushev
Journal of Multivariate Analysis 119, 61-70, 2013
90 2013 New estimators of the Pickands dependence function and a test for extreme-value dependence A Bücher, H Dette, S Volgushev
77 2011 Of copulas, quantiles, ranks and spectra: An H Dette, M Hallin, T Kley, S Volgushev
76 2015 Quantile spectral processes: Asymptotic analysis and inference T Kley, S Volgushev, H Dette, M Hallin
72 2016 When uniform weak convergence fails: Empirical processes for dependence functions and residuals via epi-and hypographs A Bücher, J Segers, S Volgushev
44 2014 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
38 2017 A subsampled double bootstrap for massive data S Sengupta, S Volgushev, X Shao
Journal of the American Statistical Association 111 (515), 1222-1232, 2016
37 2016 Weak convergence of the empirical copula process with respect to weighted metrics B Berghaus, A Bücher, S Volgushev
35 2017 Testing relevant hypotheses in functional time series via self-normalization H Dette, K Kokot, S Volgushev
arXiv preprint arXiv:1809.06092, 2018
34 2018 Equivalence of regression curves H Dette, K Möllenhoff, S Volgushev, F Bretz
Journal of the American Statistical Association 113 (522), 711-729, 2018
34 * 2018 A test for Archimedeanity in bivariate copula models A Bücher, H Dette, S Volgushev
Journal of Multivariate Analysis 110, 121-132, 2012
34 2012 Some comments on copula-based regression H Dette, R Van Hecke, S Volgushev
Journal of the American Statistical Association 109 (507), 1319-1324, 2014
33 2014 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
32 * 2022 Panel data quantile regression with grouped fixed effects J Gu, S Volgushev
Journal of Econometrics 213 (1), 68-91, 2019
32 2019 Quantile processes for semi and nonparametric regression SK Chao, S Volgushev, G Cheng
27 2017 Regulatory assessment of drug dissolution profiles comparability via maximum deviation K Moellenhoff, H Dette, E Kotzagiorgis, S Volgushev, O Collignon
Statistics in medicine 37 (20), 2968-2981, 2018
22 2018 Onset dynamics of action potentials in rat neocortical neurons and identified snail neurons: quantification of the difference M Volgushev, A Malyshev, P Balaban, M Chistiakova, S Volgushev, ...
PLoS One 3 (4), e1962, 2008
22 2008 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
20 2021 
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