Persons: Linke, Yuliana Yurievna

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Linke, Yuliana Yurievna

Statistics
in MathSciNet:	17 (17)
in zbMATH:	8 (8)
in Web of Science:	13 (13)
in Scopus:	13 (13)

Doctor of physico-mathematical sciences (2024)

Speciality:

01.01.05 (Probability theory and mathematical statistics)

Birth date:

5.05.1975

E-mail:

Subject:

nonlinear and nonparametric regression, kernel estimators, one-step estimators, change-point problem

Main publications:

Yu.Yu. Linke, Asymptotic properties of one-step M-estimators., Communications in Statistics - Theory and Methods., 48, (2019), 4096-4118
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.
Yu.Yu. Linke, I.S. Borisov, Constructing initial estimators in one-step estimation procedures of nonlinear regression, Stat. Probab. Lett., 120, (2017), 87-94
Yu.Yu. Linke, Asymptotic normality of one-step M-estimators based on non-identically distributed observations., Stat. Probab. Lett., 129, (2017), 216-221
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

https://mathscinet.ams.org/mathscinet/MRAuthorID/662637

https://orcid.org/0000-0002-5554-2830

List of publications:

scientific publications

by years

by types

by times cited

common list

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

Articles

1.	Yu. Yu. Linke, I. S. Borisov, Teor. Veroyatnost. i Primenen. (to appear)
2.	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
3.	Linke Y. , Borisov I. , Ruzankin P. , Kutsenko V., Yarovaya E., Shalnova S., “Multivariate Universal Local Linear Kernel Estimators in Nonparametric Regression: Uniform Consistency”, Mathematics, 12:12 (2024), 1890 , 23 pp.	1 ^[x]
4.	Y. Y. Linke, “On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions”, Sib. Èlektron. Mat. Izv., 21:2 (2024), 1450–1459
5.	Yu. Yu. Linke, “Towards insensitivity of Nadaraya–Watson estimators with respect to design correlation”, Theory Probab. Appl., 68:2 (2023), 198–210
6.	Yu. Yu. Linke, “On Sufficient Conditions for the Consistency of Local Linear Kernel Estimators”, Math. Notes, 114:3 (2023), 308–321
7.	Y.Y. Linke, I.S. Borisov, P.S. Ruzankin, “Universal kernel-type estimation of random fields”, Statistics, 57:4 (2023), 785-810	5 ^[x]
8.	Yu. Yu. Linke, “Mean function estimation for a noisy random process under a sparse data condition”, Chebyshevskii Sb., 24:5 (2023), 112–125
9.	Yu. Yu. Linke, I. S. Borisov, “An approach to constructing explicit estimators in nonlinear regression”, Siberian Adv. Math., 33:4 (2023), 338–346
10.	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	12 ^[x]
11.	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	15 ^[x]
12.	Yu. Yu. Linke, “Kernel estimators for the mean function of a stochastic process under sparse design conditions”, Mat. Tr., 25:2 (2022), 149–161
13.	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	14 ^[x]
14.	Yu. Yu. Linke, I. S. Borisov, “Toward the notion of intrinsically linear models in nonlinear regression”, Siberian Adv. Math., 29:3 (2019), 210-216	1 ^[x]
15.	Yu. Yu. Linke, “Asymptotic properties of one-step M-estimators”, Communications in Statistics – Theory and Methods, 48:16 (2019), 4096-4118	15 ^[x]
16.	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	2 ^[x]
17.	Yu. Yu. Linke, I. S. Borisov, “Constructing explicit estimators in nonlinear regression problems”, Theory Probab. Appl., 63:1 (2018), 22–44
18.	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
19.	Yu. Yu. Linke, “Two-step estimation in heteroscedastic linear regression model”, J. Math. Sci., 231:2 (2018), 206–217
20.	Yu. Yu. Linke, I. S. Borisov, “Constructing initial estimators in one-step estimation procedures of nonlinear regression”, Statist. Probab. Lett., 120 (2017), 87-94	22 ^[x]
21.	Yu. Yu. Linke, “Asymptotic normality of one-step M-estimators based on non-identically distributed observations”, Statist. Probab. Lett., 129 (2017), 216-221	13 ^[x]
22.	Yu. Yu. Linke, A. I. Sakhanenko, “Conditions of asymptotic normality of one-step $M$-estimators”, J. Math. Sci., 230:1 (2018), 95–111
23.	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
24.	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
25.	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
26.	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
27.	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
28.	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
29.	Yu. Yu. Linke, “On the asymptotics of distributions of two-step statistical estimates”, Siberian Math. J., 52:4 (2011), 665–681
30.	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
31.	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
32.	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
33.	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
34.	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
35.	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
36.	A. A. Borovkov, Yu. Yu. Linke, “Asymptotically optimal estimates in the smooth change-point problem”, Math. Methods of Statistics, 13:1 (2004), 1-24
37.	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
38.	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
39.	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
40.	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
41.	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

Presentations in Math-Net.Ru

1.	Об одном усилении теоремы Гаека-Шидака I. S. Borisov, Yu. Yu. Linke Applied statistics October 17, 2025 13:00
2.	О точности равномерной аппроксимации универсальными ядерными оценками гладких регрессионных функций Yu. Yu. Linke Applied statistics December 27, 2024 12:30
3.	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
4.	Универсальные ядерные оценки в непараметрической регрессии Yu. Yu. Linke November 11, 2022 15:30
5.	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
6.	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
7.	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

Organisations

Lomonosov Moscow State University, Faculty of Mechanics and Mathematics
Novosibirsk State University, Mechanics and Mathematics Department
Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk

Articles