41 citations to https://www.mathnet.ru/rus/tvp2984
  1. Ж. Спиельман, Л. Вострикова, “О проблеме разорения с инвестициями в предположении, что цены акций являются семимартингалами”, Теория вероятн. и ее примен., 65:2 (2020), 312–337  mathnet  crossref; J. Spielmann, L. Vostrikova, “On the ruin problem with investment when the risky asset is a semimartingale”, Theory Probab. Appl., 65:2 (2020), 249–269  crossref  isi  elib
  2. Beltaief S. Chernoyarov O. Pergamenchtchikov S., “Model Selection For the Robust Efficient Signal Processing Observed With Small Levy Noise”, Ann. Inst. Stat. Math., 72:5 (2020), 1205–1235  crossref  isi
  3. Ivan S. Yaroslavtsev, “Local characteristics and tangency of vector-valued martingales”, Probab. Surveys, 17:none (2020)  crossref
  4. Viktor Bezborodov, Luca Di Persio, Tyll Krueger, Pasha Tkachov, “Spatial growth processes with long range dispersion: Microscopics, mesoscopics and discrepancy in spread rate”, Ann. Appl. Probab., 30:3 (2020)  crossref
  5. Yuri Kabanov, Serguei Pergamenshchikov, “Ruin probabilities for a Lévy-driven generalised Ornstein–Uhlenbeck process”, Finance Stoch, 24:1 (2020), 39  crossref
  6. Franziska Kühn, René L. Schilling, “Strong convergence of the Euler–Maruyama approximation for a class of Lévy-driven SDEs”, Stochastic Processes and their Applications, 129:8 (2019), 2654  crossref
  7. Ivan S. Yaroslavtsev, “On the martingale decompositions of Gundy, Meyer, and Yoeurp in infinite dimensions”, Ann. Inst. H. Poincaré Probab. Statist., 55:4 (2019)  crossref
  8. Vlad Stefan Barbu, Slim Beltaief, Sergey Pergamenshchikov, “Robust adaptive efficient estimation for semi-Markov nonparametric regression models”, Stat Inference Stoch Process, 22:2 (2019), 187  crossref
  9. Yuta Koike, Zhi Liu, “Asymptotic properties of the realized skewness and related statistics”, Ann Inst Stat Math, 71:4 (2019), 703  crossref
  10. Franziska Kühn, “Existence and estimates of moments for Lévy-type processes”, Stochastic Processes and their Applications, 127:3 (2017), 1018  crossref
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