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Stanislav Volgushev
Stanislav Volgushev
Verified email at utstat.toronto.edu - Homepage
Title
Cited by
Cited by
Year
Non-crossing non-parametric estimates of quantile curves
H Dette, S Volgushev
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2008
1822008
Distributed inference for quantile regression processes
S Volgushev, SK Chao, G Cheng
1442019
Empirical and sequential empirical copula processes under serial dependence
A Bücher, S Volgushev
Journal of Multivariate Analysis 119, 61-70, 2013
982013
Quantile spectral processes: Asymptotic analysis and inference
T Kley, S Volgushev, H Dette, M Hallin
892016
New estimators of the Pickands dependence function and a test for extreme-value dependence
A Bücher, H Dette, S Volgushev
852011
Of copulas, quantiles, ranks and spectra: An -approach to spectral analysis
H Dette, M Hallin, T Kley, S Volgushev
842015
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
612022
When uniform weak convergence fails: Empirical processes for dependence functions and residuals via epi-and hypographs
A Bücher, J Segers, S Volgushev
522014
Panel data quantile regression with grouped fixed effects
J Gu, S Volgushev
Journal of Econometrics 213 (1), 68-91, 2019
512019
A subsampled double bootstrap for massive data
S Sengupta, S Volgushev, X Shao
Journal of the American Statistical Association 111 (515), 1222-1232, 2016
512016
Equivalence of regression curves
H Dette, K Möllenhoff, S Volgushev, F Bretz
Journal of the American Statistical Association 113 (522), 711-729, 2018
492018
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
452017
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
442021
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
432020
Weak convergence of the empirical copula process with respect to weighted metrics
B Berghaus, A Bücher, S Volgushev
412017
Some comments on copula-based regression
H Dette, R Van Hecke, S Volgushev
Journal of the American Statistical Association 109 (507), 1319-1324, 2014
412014
Structure learning for extremal tree models
S Engelke, S Volgushev
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022
352022
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
342020
A test for Archimedeanity in bivariate copula models
A Bücher, H Dette, S Volgushev
Journal of Multivariate Analysis 110, 121-132, 2012
342012
Quantile processes for semi and nonparametric regression
SK Chao, S Volgushev, G Cheng
Electronic Journal of Statistics 11 (2), 3272-3331, 2017
302017
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