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| 1. |
Yu. Yu. Linke, I. S. Borisov, Teor. Veroyatnost. i Primenen.   |
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 2025 |
| 2. |
I. S. Borisov, Y. Y. Linke, “Universal kernel-type estimators for the conditional variance in heteroscedastic models of nonparametric regression”, Siberian Advances in Mathematics, 35:4 (2025), 277-286 |
| 3. |
Y. Y. Linke, I. S. Borisov, P. S. Ruzankin, V. A. Kutsenko, E. B. Yarovaya, S.A. Shalnova, “Multivariate Universal Local Linear Kernel Estimators in Nonparametric Regression: Simulations and Real Data Processing”, Sankhya A., 2025, 1-28
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1
[x]
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| 2024 |
| 4. |
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  |
| 5. |
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.
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3
[x]
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| 6. |
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 |
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| 2023 |
| 7. |
Yu. Yu. Linke, “Towards insensitivity of Nadaraya–Watson estimators with respect to design correlation”, Theory Probab. Appl., 68:2 (2023), 198–210 |
| 8. |
Yu. Yu. Linke, “On Sufficient Conditions for the Consistency of Local Linear Kernel Estimators”, Math. Notes, 114:3 (2023), 308–321  |
| 9. |
Y.Y. Linke, I.S. Borisov, P.S. Ruzankin, “Universal kernel-type estimation of random fields”, Statistics, 57:4 (2023), 785-810
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7
[x]
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| 10. |
Yu. Yu. Linke, “Mean function estimation for a noisy random process under a sparse data condition”, Chebyshevskii Sb., 24:5 (2023), 112–125 |
| 11. |
Yu. Yu. Linke, I. S. Borisov, “An approach to constructing explicit estimators in nonlinear regression”, Siberian Adv. Math., 33:4 (2023), 338–346 |
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| 2022 |
| 12. |
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
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14
[x]
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| 13. |
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
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17
[x]
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| 14. |
Yu. Yu. Linke, “Kernel estimators for the mean function of a stochastic process under sparse design conditions”, Mat. Tr., 25:2 (2022), 149–161 |
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| 2021 |
| 15. |
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
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16
[x]
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| 2019 |
| 16. |
Yu. Yu. Linke, I. S. Borisov, “Toward the notion of intrinsically linear models in nonlinear regression”, Siberian Adv. Math., 29:3 (2019), 210-216
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1
[x]
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| 17. |
Yu. Yu. Linke, “Asymptotic properties of one-step M-estimators”, Communications in Statistics – Theory and Methods, 48:16 (2019), 4096-4118
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15
[x]
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| 18. |
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
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4
[x]
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| 2018 |
| 19. |
Yu. Yu. Linke, I. S. Borisov, “Constructing explicit estimators in nonlinear regression problems”, Theory Probab. Appl., 63:1 (2018), 22–44   |
| 20. |
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  |
| 21. |
Yu. Yu. Linke, “Two-step estimation in heteroscedastic linear regression model”, J. Math. Sci., 231:2 (2018), 206–217 |
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| 2017 |
| 22. |
Yu. Yu. Linke, I. S. Borisov, “Constructing initial estimators in one-step estimation procedures of nonlinear regression”, Statist. Probab. Lett., 120 (2017), 87-94
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22
[x]
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| 23. |
Yu. Yu. Linke, “Asymptotic normality of one-step M-estimators based on non-identically distributed observations”, Statist. Probab. Lett., 129 (2017), 216-221
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13
[x]
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| 2018 |
| 24. |
Yu. Yu. Linke, A. I. Sakhanenko, “Conditions of asymptotic normality of one-step $M$-estimators”, J. Math. Sci., 230:1 (2018), 95–111 |
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| 2016 |
| 25. |
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 |
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| 2014 |
| 26. |
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 |
| 27. |
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 |
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| 2013 |
| 28. |
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 |
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| 2012 |
| 29. |
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 |
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| 2011 |
| 30. |
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 |
| 31. |
Yu. Yu. Linke, “On the asymptotics of distributions of two-step statistical estimates”, Siberian Math. J., 52:4 (2011), 665–681 |
| 32. |
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 |
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| 2010 |
| 33. |
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 |
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| 2009 |
| 34. |
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 |
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| 2008 |
| 35. |
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 |
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| 2006 |
| 36. |
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 |
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| 2005 |
| 37. |
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 |
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| 2004 |
| 38. |
A. A. Borovkov, Yu. Yu. Linke, “Asymptotically optimal estimates in the smooth change-point problem”, Math. Methods of Statistics, 13:1 (2004), 1-24 |
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| 2003 |
| 39. |
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 |
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| 2001 |
| 40. |
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 |
| 41. |
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 |
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| 2000 |
| 42. |
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 |
| 43. |
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 |
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