Stanislav Volgushev




Office hours:

By appointment

Research Interests:

Quantile regression, nonparametric statistics, censored data, copulas.

Statistical Consulting

Statistical Consulting

Publications

Published Papers:

Berghaus, B., Bücher, A. and Volgushev, S. (2015+). Weak convergence of the empirical copula process with respect to weighted metrics. To appear in Bernoulli.

Dette, H., Titoff, S., Volgushev, S. and Bretz, F. (2015+). Dose response signal detection under model uncertainty. To appear in Biometrics.

Kley, T., Volgushev, S., Dette, H. and Hallin, M. (2015+). Quantile spectral processes: Asymptotic analysis and inference. To appear in Bernoulli.

Huang, Y., Volgushev, S. and Shao, X. (2015+). On self-normalization for censored dependent data. To appear in Journal of Time Series Analysis.

Dette, H., Hallin, M., Kley, T. and Volgushev, S. (2015). Of copulas, quantiles, ranks and spectra: An $L_1$-approach to spectral analysis. Bernoulli, Vol. 21(2), 781-831.

Volgushev, S., Wagener, J. und Dette, H. (2014). Censored quantile regression processes under dependence and penalization. Electronic Journal of Statistics, Vol. 8(2), 2405-2447.

Dette, H., Van Hecke, R. and Volgushev, S. (2014). Some comments on copula-based regression. Journal of the American Statistical Association, Vol. 109(507), 1319-1324.

Volgushev, S. and Shao, X. (2014). A general approach to the joint asymptotic analysis of statistics from sub-samples. Electronic Journal of Statistics, Vol. 8, 390-431.

Bücher, A., Segers, J. und Volgushev, S. (2014). When uniform weak convergence fails: Empirical processes for dependence functions and residuals via epi- and hypographs. Annals of Statistics, Vol. 42(4), 1598-1634.

Malyshev, A., Tchumachenko, T., Volgushev, S. and Volgushev, M. (2013). Energy-efficient encoding by shifting spikes in neocortical neurons. European Journal of Neuroscience , Vol. 38, 3181-3188.

Volgushev, S. and Dette, H. (2013). Nonparametric quantile regression for twice censored data. Bernoulli, Vol. 19(3), 748-779.

Bücher, A. and Volgushev, S. (2013). Empirical and sequential empirical copula processes under serial dependence. Journal of Multivariate Analysis, Vol. 119, 61-70.

Dette, H., Wagener, J. and Volgushev, S. (2013). Nonparametric comparison of quantile curves: A stochastic process approach. Journal of Nonparametric Statistics , Vol. 25(1), 243-260.

Volgushev, S., Birke, M., Dette, H and Neumeyer, N. (2013). Significance testing in quantile regression. Electronic Journal of Statistics, Vol. 7, 105-145.

Bücher, A., Dette, H. und Volgushev, S. (2012). A test for Archimedeanity in bivariate copula models. Journal of Multivariate Analysis, Vol. 110, 121-132.

Wagener, J., Volgushev, S. and Dette, H. (2012). The quantile process under random censoring, Mathematical Methods of Statistics, Vol. 21(2), 127-141.

Bücher, A., Dette, H. and Volgushev, S. (2011). New estimators of the Pickands dependence function and a test for extreme-value dependence. Annals of Statistics, Vol. 39, No. 4, 1963-2006.

Dette, H., Wagener, J. and Volgushev, S. (2011). Comparing conditional quantile curves. Scandinavian Journal of Statistics , Vol. 38, 63-88.

Hoch, T., Volgushev, S., Malyshev, A., Obermayer, K. and Volgushev, M. (2011). Modulation of the amplitude of γ-band activity by stimulus phase enhances signal encoding. European Journal of Neuroscience, Vol. 33, 1223-1239.

Dette, H. and Volgushev, S. (2008). Non-crossing nonparametric estimates of quantile curves, Journal of the Royal Statistical Society: Series B, Vol. 70(3), 609-627.

Volgushev, M., Malyshev, A., Balaban, P., Chistiakova, M., Volgushev, S., et al. (2008). Onset Dynamics of Action Potentials in Rat Neocortical Neurons and Identified Snail Neurons: Quantification of the Difference. PLoS ONE 3(4): e1962. doi:10.1371/journal.pone.0001962

Submitted:

Dette, H., Möllenhoff, K., Volgushev, S. and Bretz, F. (2015). Equivalence of dose response curves (PDF).

Skowronek, S,. Volgushev, S., Kley, T., Dette, H. and Hallin, M. (2014). Quantile spectral analysis for locally stationary time series (PDF).

Birke, M., Neumeyer, N. and Volgushev, S. (2013). The independence process in conditional quantile location-scale models and an application to testing for monotonicity, (PDF)

Gu, J., Koenker, R. and Volgushev, S. (2013). Testing for homogeneity in mixture models, (PDF)

Volgushev, S. (2013). Smoothed quantile regression processes for binary response models, (PDF)

Gralla, R., Kraft, K. and Volgushev, S. (2012). The effects of works councils on overtime hours - a censored quantile regression approach, (PDF)