@article{oai:senshu-u.repo.nii.ac.jp:00011036,
 author = {石鎚, 英也},
 journal = {専修ネットワーク&インフォメーション, Network and Information},
 month = {Mar},
 note = {In the world of games and sports, various rating methods have been developed and used in order to rank players or teams according to their real abilities - Elo rating in chess and Massey rating in college football, for instance. Players and teams are re-rated according to the results of matches, and rating scores and rankings can be updated instantly. However, the followings may be pointed out as drawbacks of prevailing rating methods: It possibly takes time to get stable rating values. It is difficult to properly set parameters included in the updating formulae. And rating values tend to be inflationary.
In this study, traditional and standard rating methods are extended by Bayesian statistical modeling so as to mitigate such drawbacks. Then, they are applied to real records of games and sports.},
 pages = {1--16},
 title = {レイティングのベイズ統計モデリング},
 volume = {28},
 year = {2020}
}