• seit Apr 2016: Postdoc am Institut für Stochastik, Universität Ulm

• Okt 2015 - Mär 2016: Postdoc an der Nationale Taras-Schewtschenko-Universität Kiew

• Okt 2012 - Okt 2015: Doktorand an der Nationale Taras-Schewtschenko-Universität Kiew

• Sep 2009 - Jun 2011: Master of Science an der Nationale Taras-Schewtschenko-Universität Kiew

• Sep 2005 - Jun 2009: Bachelor of Science an der Nationale Taras-Schewtschenko-Universität Kiew

2021

• Das, A., Makogin, V., & Spodarev, E. (2021). Extrapolation of Stationary Random Fields Via Level Sets. arXiv preprint arXiv:2108.12481.
• Makogin, V., & Spodarev, E. (2021). Limit theorems for excursion sets of subordinated Gaussian random fields with long-range dependence. Stochastics, 1-32.
• Makogin, V., Mishura, Y., & Zhelezniak, H. (2021). Approximate solution of the integral equations involving kernel with additional singularity. Stochastic Models, 1-19.
• Makogin, V., Oesting M., Rapp, A., Spodarev, (2021) E. Long Range Dependence for Stable Random Processes,  J. Time Ser. Anal. 42: 161–185 DOI: 10.1111/jtsa.12560

2020

• Leonenko, N., Makogin, & V. Cadirci, M. S.,(2020). The entropy based goodness of fit tests for generalized von Mises-Fisher distributions and beyond. arXiv preprint arXiv:2010.10918 [math.ST]

• Cadirci, M. S., Evans, D., Leonenko, N., & Makogin, V. (2020). Entropy-based test for generalized Gaussian distributions. arXiv preprint arXiv:2010.06284 [math.ST]

• Makogin V., Mishura Yu., (2020) Fractional integrals, derivatives and integral equations with weighted Takagi–Landsberg functions. Nonlinear Analysis: Modelling and Control, 25(6), 1079-1106.

• Dresvyanskiy, D., Karaseva, T., Makogin, V., Mitrofanov, S., Redenbach, C., & Spodarev, E. (2020). Detecting anomalies in fibre systems using 3-dimensional image data. Statistics and Computing. https://doi.org/10.1007/s11222-020-09921-1.

• Makogin V., Mishura Yu. (2020) Small deviations for mixed fractional Brownian motion with trend and with Hurst index H>1/2, Stochastics, 92(5), 746-760, DOI: 10.1080/17442508.2019.1652609
   
• Makogin V. I., Mishura Yu. S., Zhelezniak H. S. (2020) Minimization of the entropy for a mixture of standard and fractional Brownian motions. Theory of Probability and Mathematical Statistics, 101, 193-215.

2019

• Vitalii Makogin & Yuliya Mishura (2019) Gaussian multi-self-similar random fields with distinct stationary properties of their rectangular increments, Stochastic Models, 35(4), 391-428, DOI: 10.1080/15326349.2019.1610664
• Dresvyanskiy, D., Karaseva, T., Mitrofanov, S., Redenbach, C., Schwaar, S., Makogin, V., & Spodarev, E. (2019, May). Application of clustering methods to anomaly detection in fibrous media. In IOP Conference Series: Materials Science and Engineering (Vol. 537, No. 2, p. 022001). IOP Publishing.

2017

• Makogin, V., Melnikov., A., Mishura, Yu. On Mean-variance hedging under partial obesrvations and terminal wealth constraints. International Journal of Theoretical and Applied Finance 20(5), 1750031 (2017).

2016

• Makogin, V. Simulation paradoxes related to a fractional Brownian motion with small Hurst index. Modern Stochastics: Theory and Applications 2.3, 181-190 (2016).

2015

• Makogin, V., and Mishura, Yu. Example of a Gaussian self-similar field with stationary rectangular increments that is not a fractional Brownian sheet. Stochastic Analysis and Applications, 33 (3), 413-428 (2015).
• Makogin, V.I., Asymptotic properties of integral functionals of fractional Brownian fields. Theor. Probability and Math. Statist. 91, 105-114 (2015)

2014

• Kozachenko, Y., and Makogin, V. Probability distributions of extremes of self-similar Gaussian random fields. Journal of Classical Analysis, 5(1), 25-42 (2014).
• Makogin, V., and Mishura, Yu. Strong limit theorems for anisotropic self-similar fields. Modern Stochastics: Theory and Applications 1.1, 73-93 (2014).

2013

• Makogin, V.I., Mishura, Yu.S., Shevchenko, G.M., Zolota, A.V.: Asymptotic behaviour of the trajectories of the fractional Brownian motion, anisotropic fractional Brownian field and their fractional derivatives. Appl. Stat. Actuar. Financ. Math. 1–2, 110–115 (2013). (In Ukrainian)

Prediction of random time series via the excursion metric:
 - R code, August 2022