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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
1652008
Distributed inference for quantile regression processes
S Volgushev, SK Chao, G Cheng
The Annals of Statistics 47 (3), 1634-1662, 2019
912019
Empirical and sequential empirical copula processes under serial dependence
A Bücher, S Volgushev
Journal of Multivariate Analysis 119, 61-70, 2013
882013
New estimators of the Pickands dependence function and a test for extreme-value dependence
A Bücher, H Dette, S Volgushev
The Annals of Statistics 39 (4), 1963-2006, 2011
782011
Of copulas, quantiles, ranks and spectra: An -approach to spectral analysis
H Dette, M Hallin, T Kley, S Volgushev
Bernoulli 21 (2), 781-831, 2015
732015
Quantile spectral processes: Asymptotic analysis and inference
T Kley, S Volgushev, H Dette, M Hallin
Bernoulli 22 (3), 1770-1807, 2016
672016
When uniform weak convergence fails: Empirical processes for dependence functions and residuals via epi-and hypographs
A Bücher, J Segers, S Volgushev
The Annals of Statistics 42 (4), 1598-1634, 2014
412014
A subsampled double bootstrap for massive data
S Sengupta, S Volgushev, X Shao
Journal of the American Statistical Association 111 (515), 1222-1232, 2016
382016
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
372017
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
Weak convergence of the empirical copula process with respect to weighted metrics
B Berghaus, A Bücher, S Volgushev
Bernoulli 23 (1), 743-772, 2017
332017
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
322020
Panel data quantile regression with grouped fixed effects
J Gu, S Volgushev
Journal of Econometrics 213 (1), 68-91, 2019
322019
A test for Archimedeanity in bivariate copula models
A Bücher, H Dette, S Volgushev
Journal of Multivariate Analysis 110, 121-132, 2012
322012
Some comments on copula-based regression
H Dette, R Van Hecke, S Volgushev
Journal of the American Statistical Association 109 (507), 1319-1324, 2014
312014
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
29*2022
Quantile processes for semi and nonparametric regression
SK Chao, S Volgushev, G Cheng
Electronic Journal of Statistics 11 (2), 3272-3331, 2017
272017
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
242008
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
222018
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
192020
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