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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/158757
Title: Classification and Prediction of the Gaming Activity States in Online- Games Based on the Regime Switching Models
Authors: Malugin, V.
Babakhin, Y.
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Информатика
ЭБ БГУ::ТЕХНИЧЕСКИЕ И ПРИКЛАДНЫЕ НАУКИ. ОТРАСЛИ ЭКОНОМИКИ::Медицина и здравоохранение
Issue Date: 2016
Publisher: Minsk: Publishing Center of BSU
Abstract: The goal of the study is to construct an algorithm of determining the overall gaming activity state in online-games. Apart from the classification of states, the problem of predicting future gaming activity states has arisen. Both goals are accomplished by using multivariate econometric models with heterogeneous structure and the assumption of the hidden Markov dependency of the classes of states. In particular, Markov-Switching Vector Autoregression Models (MSVAR) have been used. The constructed theoretical methods have been applied to the measuring gaming activity in the famous online-game: "World of Tanks".
URI: http://elib.bsu.by/handle/123456789/158757
Appears in Collections:2016. PATTERN RECOGNITION AND INFORMATION PROCESSING (PRIP’2016)

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