Timur Khusyainov, Deputy Dean of theFaculty of Humanities atHSE University–Nizhny Novgorod, took part in two international conferences—the XVI World Congress of Rural Sociology in Porto Alegre, Brazil, and the 36th Annual Conference of the Alliance of Digital Humanities Organisations (DH2026) in Daejeon, South Korea. On his way to the conferences, the researcher also visited several other places, where he presented the experience of the Pochtovoe educational project.
Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.
Anastasia Gergenreter specialises in applied statistics and econometrics. In this interview for the Young Scientists of HSE University project, she talked about why she studies addictive substance use, two very different Fishers, and the cherry blossom season at the Main Botanical Garden in Moscow.
Goryainova E. R., Botvinkin E. A., Automation and Remote Control 2017 Vol. 78 No. 10 P. 1819–1836
We consider LS-, LAD-, R-, M-, S-, LMS-, LTS-, MM-, and HBR-estimates for the parameters of a linear regression model with unknown noise distribution. With computer modeling for medium sized samples, we compare the accuracy of the considered estimates for the most popular probability distributions of noise in a regression model. For different noise distributions, ...
Shvedov A. S., Экономический журнал Высшей школы экономики 2011 Т. 15 № 1 С. 68–87
The paper deals with a linear regression model. The EM algorithm is popular tool for maximum likelihood estimation of the parameters of regression model. It provides a method of robust regression under the assumption that the disturbances are independent and have identical multivariate t distribution. Previous work focused on the method of maximum likelihood estimation ...