2023-06-10T23:59:44Zhttps://osu.repo.nii.ac.jp/?action=repository_oaipmhoai:osu.repo.nii.ac.jp:000002082017-12-15T07:12:08Z00020:00099:00098
大規模データに対するべき分布性の確認方法Verifying Power-Law Distribution in Empirical Datajpnべき分布離散コルモゴロフ-スミルノフ検定最尤法Power-Law DistributioDiscreteKolmogorov-Smirnov TestMaximum Likelihoodhttp://id.nii.ac.jp/1338/00000200/Departmental Bulletin PaperP(論文)論文Article井上, 寛康イノウエ, ヒロヤスHiroyasu, INOUE大阪産業大学経営学部流通学科In social science, it is mostly assumed that there is a typical value for data. This is because normal distribution is supposed. However, it is hardly possible that all data in the natural world as well as human society obey normal distribution. Hence, if people take data for some phenomenon and suppose the data obeys normal distribution, that can lead to a wrong conclusion. In fact, people can have accessed many large scale empirical data in recent years and found those distributions do not obey normal distribution. Some of them obey power-law distribution whose nature has been recently well studied. This paper studied whether the distribution of joint patent applications for an organization obeys power-law distribution or not. The distribution is far from normal distribution and looks like power-law distribution. Hence, it was judged whether the distribution obeys power-law distribution using Clauset's method. The results showed the distribution in 7 and over obeys power-law distribution, and the exponent is 3.03.AA11394617大阪産業大学経営論集1121651762010-02https://osu.repo.nii.ac.jp/?action=repository_action_common_download&item_id=208&item_no=1&attribute_id=18&file_no=12015-08-03