Understanding the concept of outlier and its relevance to the assessment of data quality: Probabilistic background theory
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- Monhor Davaadorjin
- Department of Geophysics, Graduate School of Science, Kyoto University
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- Takemoto Shuzo
- Department of Geophysics, Graduate School of Science, Kyoto University
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説明
In recent years an increasing interest in the studies on outlier can be observed, however, for the time being there exists no general definition of outlier. In the present paper we introduced a generic descriptive definition of outlier. We observed that the outlier problems had so far been treated in statistical way without paying proper attention to probabilistic-theoretic backgrounds. In view of this gap, we made an attempt to establish a probabilistic background theory. Within this framework, the large deviations are considered as probabilistic-theoretic model of outlier, and the interrelationship of the laws of large numbers, the central limit theorems and the large deviations are clarified. These considerations are specialized for the case of statistical sample, which is important from the point of view of the assessment of data quality. Some methodological and historical aspects of geodesy, geophysics and astronomy are mentioned, too. We revealed that the data analysis carried out by Kepler in the process of discovery of his famous elliptic law of planetary motion has relevance to the outlier problem. This methodologically interesting fact is a new result in the history of geosciences. We established that the accuracy of Chebyshev inequality increases as the deviation of the random variable involved from its expectation, increases. The possibility of application of Chebyshev inequality to the outlier problem is pointed out.
収録刊行物
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- Earth, Planets and Space
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Earth, Planets and Space 57 (11), 1009-1018, 2005
地球電磁気・地球惑星圏学会 、公益社団法人 日本地震学会、特定非営利活動法人 日本火山学会、日本測地学会、日本惑星科学会
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詳細情報 詳細情報について
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- CRID
- 1390282681488296960
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- NII論文ID
- 10017470714
- 130003956445
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- NII書誌ID
- AA11211921
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- ISSN
- 18805981
- 13438832
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- NDL書誌ID
- 7737240
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
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