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Linke, Yuliana Yurievna

Total publications: 37 (37)
in MathSciNet: 17 (17)
in zbMATH: 8 (8)
in Web of Science: 13 (13)
in Scopus: 13 (13)
Cited articles: 29
Citations: 215
Presentations: 5

Number of views:
This page:1693
Abstract pages:7271
Full texts:1898
References:864
Senior Researcher
Candidate of physico-mathematical sciences (2000)
Speciality: 01.01.05 (Probability theory and mathematical statistics)
Birth date: 5.05.1975
E-mail:
Website: https://tvims.nsu.ru/linke/
   
Main publications:
  1. Yu.Yu. Linke, Asymptotic properties of one-step M-estimators., Communications in Statistics - Theory and Methods., 48, (2019), 4096-4118
  2. Linke Y., Borisov I., Ruzankin P., Kutsenko V., Yarovaya E., Shalnova S., “Universal local linear kernel estimators in nonparametric regression”, Mathematics, 10:15 (2022), 2693.
  3. Yu.Yu. Linke, I.S. Borisov, Constructing initial estimators in one-step estimation procedures of nonlinear regression, Stat. Probab. Lett., 120, (2017), 87-94
  4. Yu.Yu. Linke, Asymptotic normality of one-step M-estimators based on non-identically distributed observations., Stat. Probab. Lett., 129, (2017), 216-221
  5. Yu.Yu. Linke, I.S,Borisov, “Insensitivity of Nadaraya–Watson estimators to design correlation”, Communications in Statistics - Theory and Methods, 51:19 (2022), 6909-6918

https://www.mathnet.ru/eng/person17819
List of publications on Google Scholar
List of publications on ZentralBlatt
https://mathscinet.ams.org/mathscinet/MRAuthorID/662637

Full list of publications:
| scientific publications | by years | by types | by times cited | common list |


Citations (Crossref Cited-By Service + Math-Net.Ru)

   2024
1. Yu. Yu. Linke, I. S. Borisov, “Universal nonparametric kernel-type estimators for the mean and covariance functions of a stochastic process”, Theory Probab. Appl., 69:1 (2024), 35–58  mathnet  crossref  crossref  scopus

   2023
2. Yu. Yu. Linke, “Towards insensitivity of Nadaraya–Watson estimators with respect to design correlation”, Theory Probab. Appl., 68:2 (2023), 198–210  mathnet  crossref  crossref  scopus
3. Yu. Yu. Linke, “On Sufficient Conditions for the Consistency of Local Linear Kernel Estimators”, Math. Notes, 114:3 (2023), 308–321  mathnet  crossref  crossref  crossref  mathscinet  scopus
4. Y.Y. Linke, I.S. Borisov, P.S. Ruzankin, “Universal kernel-type estimation of random fields”, Statistics, 57:4 (2023), 785-810  crossref 4
5. Yu. Yu. Linke, “Mean function estimation for a noisy random process under a sparse data condition”, Chebyshevskii Sb., 24:5 (2023), 112–125  mathnet  crossref

   2022
6. Yu. Yu. Linke, I. S. Borisov, “Insensitivity of Nadaraya–Watson estimators to design correlation”, Communications in Statistics – Theory and Methods, 51:19 (2022), 6909–6918  crossref 10
7. Y. Linke, I. Borisov, P. Ruzankin, V. Kutsenko, E. Yarovaya, S. Shalnova., “Universal local linear kernel estimators in nonparametric regression”, Mathematics, 10:15 (2022), 2693  crossref 13
8. Yu. Yu. Linke, “Kernel estimators for the mean function of a stochastic process under sparse design conditions”, Mat. Tr., 25:2 (2022), 149–161  mathnet  crossref

   2021
9. I. S. Borisov, Yu. Yu. Linke, P. S. Ruzankin, “Universal weighted kernel-type estimators for some class of regression models”, Metrika, 84:2 (2021), 141-166  crossref 12

   2019
10. Yu. Yu. Linke, I. S. Borisov, “Toward the notion of intrinsically linear models in nonlinear regression”, Siberian Adv. Math., 29:3 (2019), 210-216  crossref 1
11. Yu. Yu. Linke, “Asymptotic properties of one-step M-estimators”, Communications in Statistics – Theory and Methods, 48:16 (2019), 4096-4118  crossref 13
12. Yu.Yu. Linke, “Kernel estimators for the mean function of a stochastic process under sparse design conditions”, Siberian Advances in Mathematics, 32:4 (2019), 269–276  crossref 1

   2018
13. Yu. Yu. Linke, I. S. Borisov, “Constructing explicit estimators in nonlinear regression problems”, Theory Probab. Appl., 63:1 (2018), 22–44  mathnet  crossref  crossref  isi  elib  scopus
14. Yu. Yu. Linke, “Asymptotic properties of one-step weighted $M$-estimators with application to some regression problems.”, Theory Probab. Appl., 62:3 (2018), 373–398  mathnet  crossref  crossref  mathscinet  zmath  isi  elib  scopus
15. Yu. Yu. Linke, “Two-step estimation in heteroscedastic linear regression model”, J. Math. Sci., 231:2 (2018), 206–217  mathnet  crossref  crossref  elib

   2017
16. Yu. Yu. Linke, I. S. Borisov, “Constructing initial estimators in one-step estimation procedures of nonlinear regression”, Statist. Probab. Lett., 120 (2017), 87-94  crossref 20
17. Yu. Yu. Linke, “Asymptotic normality of one-step M-estimators based on non-identically distributed observations”, Statist. Probab. Lett., 129 (2017), 216-221  crossref 10

   2018
18. Yu. Yu. Linke, A. I. Sakhanenko, “Conditions of asymptotic normality of one-step $M$-estimators”, J. Math. Sci., 230:1 (2018), 95–111  mathnet  crossref  crossref  elib

   2016
19. Yu. Yu. Linke, “Refinement of Fisher’s one-step estimators in the case of slowly converging preliminary estimators”, Theory Probab. Appl., 60:1 (2016), 88–102  mathnet  crossref  crossref  mathscinet  isi  elib  scopus

   2014
20. Yu. Yu. Linke, A. I. Sakhanenko, “On conditions for asymptotic normality of Fisher's one-step estimators in one-parameter families of distributions”, Sib. Èlektron. Mat. Izv., 11 (2014), 464–475  mathnet
21. Yu. Yu. Linke, A. I. Sakhanenko, “On asymptotics of the distributions of some two-step statistical estimators of a mutlidimensional parameter”, Siberian Adv. Math., 24:2 (2014), 119–139  mathnet  crossref  mathscinet  elib

   2013
22. Yu. Yu. Linke, A. I. Sakhanenko, “On asymptotics of the distribution of a two-step statistical estimator of a one-dimensional parameter”, Sib. Èlektron. Mat. Izv., 10 (2013), 627–640  mathnet

   2012
23. Yu. Yu. Linke, A. I. Sakhanenko, “On solutions to the equation for improving additives in regression problems”, Siberian Adv. Math., 22:4 (2012), 261–274  mathnet  crossref  mathscinet  elib

   2011
24. A. I. Sakhanenko, Yu. Yu. Linke, “Consistent estimation in a linear regression problem with random errors in coefficients”, Siberian Math. J., 52:4 (2011), 711–726  mathnet  crossref  mathscinet  isi  elib  elib  scopus
25. Yu. Yu. Linke, “On the asymptotics of distributions of two-step statistical estimates”, Siberian Math. J., 52:4 (2011), 665–681  mathnet  crossref  mathscinet  isi  scopus
26. A. I. Sakhanenko, Yu. Yu. Linke, “Improvement of estimators in a linear regression problem with random errors in coefficients”, Siberian Math. J., 52:1 (2011), 113–126  mathnet  crossref  mathscinet  isi  scopus

   2010
27. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically optimal estimation in a linear regression problem with random errors in coefficients”, Siberian Math. J., 51:1 (2010), 104–118  mathnet  crossref  mathscinet  isi  scopus

   2009
28. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically optimal estimation in the linear regression problem in the case of violation of some classical assumptions”, Siberian Math. J., 50:2 (2009), 302–315  mathnet  crossref  mathscinet  isi  scopus

   2008
29. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically normal estimation in the linear-fractional regression problem with random errors in coefficients”, Siberian Math. J., 49:3 (2008), 474–497  mathnet  crossref  mathscinet  zmath  isi  scopus

   2006
30. A. I. Sakhanenko, Yu. Yu. Linke, “Asymptotically optimal estimation in a linear-fractional regression problem with random errors in coefficients”, Siberian Math. J., 47:6 (2006), 1128–1153  mathnet  crossref  mathscinet  zmath  isi  scopus

   2005
31. A. A. Borovkov, Yu. Yu. Linke, “Change-point problem for large samples and incomplete information on distribution”, Math. Methods of Statistics, 14:4 (2005), 404-430

   2004
32. A. A. Borovkov, Yu. Yu. Linke, “Asymptotically optimal estimates in the smooth change-point problem”, Math. Methods of Statistics, 13:1 (2004), 1-24

   2003
33. I. V. Askarova, Yu. Yu. Linke, “On conditions for the asymptotic normality of estimates of the second step in a linear-fractional regression problem”, Sib. Zh. Ind. Mat., 6:3 (2003), 8–17  mathnet  mathscinet  zmath

   2001
34. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically normal explicit estimation of parameters in the Michaelis–Menten equation”, Siberian Math. J., 42:3 (2001), 517–536  mathnet  crossref  mathscinet  zmath  isi
35. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically normal estimation of a multidimensional parameter in the linear-fractional regression problem”, Siberian Math. J., 42:2 (2001), 317–331  mathnet  crossref  mathscinet  zmath  isi

   2000
36. Yu. Yu. Linke, “Explicit asymptotically normal estimation of the parameter for a multidimensional nonlinear regression problem”, Sib. Zh. Ind. Mat., 3:1 (2000), 157–164  mathnet  mathscinet  zmath
37. Yu. Yu. Linke, A. I. Sakhanenko, “Asymptotically normal estimation of a parameter in a linear-fractional regression problem”, Siberian Math. J., 41:1 (2000), 125–137  mathnet  crossref  mathscinet  zmath  isi

Presentations in Math-Net.Ru
1. Универсальные ядерные оценки в непараметрической регрессии с приложениями к нелинейным регрессионным моделям
Yu. Yu. Linke
Principle Seminar of the Department of Probability Theory, Moscow State University
December 13, 2023 16:45
2. Универсальные ядерные оценки в непараметрической регрессии
Yu. Yu. Linke

November 11, 2022 15:30   
3. Универсальные локально-постоянные и локально-линейные ядерные оценки в непараметрической регрессии
Yu. Yu. Linke
Principle Seminar of the Department of Probability Theory, Moscow State University
March 2, 2022 16:45   
4. Построение явных оценок в задачах нелинейной регрессии с приложениями к непараметрическим регрессионным моделям
Yu. Yu. Linke
Principle Seminar of the Department of Probability Theory, Moscow State University
April 21, 2021 16:45   
5. Асимптотические свойства одношаговых $M$-оценок с приложениями к задачам регрессии
Yu. Yu. Linke
Seminar on Probability Theory and Mathematical Statistics
April 29, 2016 18:00

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