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2019. Computer Data Analysis and Modeling : Stochastics and Data Science : [74] Collection home page


This collection of papers includes proceedings of the Twelfth International Conference “Computer Data Analysis and Modeling: Stochastics and Data Science” organized by the Belarusian State University and held in September 2019 in Minsk. Papers are reviewed by qualified researchers from Austria, Belarus, Lithuania, Russia, Ukraine.

The papers are devoted to the topical problems: robust and nonparametric data analysis; statistical analysis of time series and forecasting; multivariate data analysis; design of experiments; probability and statistical analysis of discrete data; econometric analysis and modeling; survey analysis and official statistics; computer intensive methods, algorithms and software; computer data analysis in applications.

For specialists who work in the fields of mathematical statistics and its applications, computer data analysis, data science and statistical software development.

При полном или частичном использовании материалов ссылка на сайт Электронной библиотеки БГУ (www.elib.bsu.by) обязательна.

Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 74
PreviewIssue DateTitleAuthor(s)
2019Discrete-valued time series analysis by parsimonious high-order Markov chainsKharin, Yu. S.
2019Multiclass support vector machines with GenSVMGroenen, P. J. F.; van den Burg, G. J. J.
2019Number of pairs of identically marked templates in q-ary treeZubkov, A. M.; Kruglov, V. I.
2019Formula for European options costs calculationZuev, N. M.
2019A random graph generation model for transcription networks and nonparametric simulator for RNA-seq expression dataGrimes, T.; Datta, S.
2019Regenerative simulation of time-sharing queueing system in random environmentZorine, A. V.
2019Implementation of generalized additive models for spatial beta regressionZikariene, E.; Ducinskas, K.
2019Stochastic analysis of the smooth number properties and their searchVostrov, G.; Ponomarenko, O.
2019Non-asymptotic confidence estimation of the autoregressive parameter in AR(1) process with an unknown noise varianceVorobeychikov, S. E.; Burkatovskaya, Yu. B.
2019On some upper bounds for noncentral chi-square cdfVoloshko, V. A.; Vecherko, E. V.
2019A generalized probabilistic model of computer proof of the Artin hypothesisVostrov, G.; Opiata, R.
2019Principle components method in statistical classification and its efficiencyZhuk, E. E.
2019Some formulas of operator interpolation on the set of random processesYanovich, L. A.; Ignatenko, M. V.
2019Empirical likelihood confidence intervals for censored integralsZakhidov, D. G.; Iskandarov, D. Kh.
2019Internally homogeneous random fields analysisTsekhavaya, T. V.; Troush, N. N.
2019Meteorological data influence on missing vessel type detection using deep multi-stacked LSTM neural networkVenskus, J.; Treigys, P.
2019A set of asymptotically independent statistics of polynomial frequencies containing the Pearson statisticSavelov, M. P.
2019Conformal predictors for reliable pattern recognitionGammerman, A.
2019Structural distribution estimationRadavicius, M.
2019Drift parameter estimation in Gaussian regression model by continuous and discrete observationsRalchenko, K.
Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 74