Papers in Refereed Journals and Submitted:

  1. Miller, J. and Stepanova, N. (2022+). Sparse signal recovery with Subbotin noise, submitted to Statistics and Probability Letters.
  2. Pavlenko, T., Stepanova, N., and Thompson, L. (2022). Adaptive threshold-based classification of sparse high-dimensional data. Electronic Journal of Statistics, 16: 1952-1996.
  3. Wang, Y. and Stepanova, N. (2021). Estimating the amount of sparsity in two-point mixture models. Zapiski Nauchnyh Seminarov POMI, a special volume in memory of Yakov Nikitin, 51: 78-101.
  4. Butucea, C., Ndaoud, M., Stepanova, N., and Tsybakov, A. (2018). Variable selection with Hamming loss. Annals of Statistics, 46 (5): 1837-1875.
  5. Stepanova, N. and Pavlenko T. (2018). Goodness-of-fit tests based on sup-functionals of weighted empirical processes. Theory of Probability and Its Applications, 63 (2): 358-388.
  6. Butucea, C. and Stepanova, N. (2017). Adaptive variable selection in nonparametric sparse additive models. Electronic Journal of Statistics 11 (1): 2321-2357.
  7. Stepanova, N. and Tsybakov, A. (2016). Discussion of influential features PCA for high dimensional clustering, by J. Jin and W. Wang. Annals of Statistics, 44 (6), 2382-2386.
  8. Kosta, O. and Stepanova, N. (2015). Efficient density estimation and value at risk using Fejér-type kernel functions. Journal of Mathematical Finance, 5: 480-504.
  9. Borodin, A. N., Golubev, G. K., Ermakov, M. S., Zaitsev, A. Yu., Ibragimov, I. A., Kutoyants, Yu. A., Lepski, O. V., Lifshits, M. A., Nikitin, Ya. Yu., Spokoiny, V. G., Stepanova, N. A., Tsybakov, A. B. (2015). To the Memory of Yu. I. Ingster. Journal of Mathematical Sciences, 204 (1): 1-6. (Russian version in Zap. Nauchn. Sem. POMI (2013), 412: 5-14.)
  10. Ingster, Yu. and Stepanova, N. (2014). Adaptive variable selection in nonparametric sparse regression. Journal of Mathematical Sciences, 199 (2): 184-201 (Russian version in Zap. Nauchn. Sem. POMI, Festschrift for Ildar Ibragimov (2012), 408: 214-244.)
  11. Stepanova, N. (2013). On estimation of analytic density functions in $L_p$. Mathematical Methods of Statistics, 22: 114-136.
  12. Nazarov, A. and Stepanova, N. (2012). An extremal problem with applications to the problem of testing multivariate independence. Journal of Nonparametric Statistics, 24 (1): 3-17.
  13. Ingster, Yu. and Stepanova, N. (2011). Estimation and detection of functions from anisotropic Sobolev classes. Electronic Journal of Statistics, 5: 484-506.
  14. Ingster, Yu. and Stepanova, N. (2009). Estimation and detection of analytic functions from weighted tensor product spaces. Mathematical Methods of Statistics, 18 (4): 310-340
  15. Stepanova, N. and Wang, S. (2008). Asymptotic efficiency of the Blest type tests for independence, Australian & New Zealand Journal of Statistics, 50 (3): 217-233.
  16. Levit, B. and Stepanova, N. (2004). Efficient estimation of multivariate analytic functions in cube-like domains, Mathematical Methods of Statistics, 13: 253-281.
  17. Stepanova, N. (2003). Multivariate Kendall's and Spearman's tests for independence and their asymptotic efficiency, Mathematical Methods of Statistics 12: 197-217.
  18. Nikitin, Ya. and Stepanova, N. (2003). Pitman efficiency of tests for independence based on weighted rank statistics, Journal of Mathematical Sciences, 118: 5596-5606.
  19. Nikitin, Ya. and Stepanova, N. (2000). A generalization of Kendall's tau and asymptotic efficiency of the corresponding test of independence, Journal of Mathematical Sciences, 99: 1154-1160.
  20. Nikitin, Ya. and Stepanova, N. (1999). Tests of independence based on generalized correlation coefficients and their asymptotic efficiency, Vestnik of St.Petersburg University, Mathematics, 32 (4): 54-59.