A New Approach to Astronomical Data Analysis Based on Multiple Variables
Data analysis for a sample of celestial bodies generally is preceded by the completeness test in order to verify whether the sample objects are proper representatives of the corresponding part of the universe. A data set following a multivariate, continuous, uniform distribution is said to be “compl...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Advances in Astronomy |
| Online Access: | http://dx.doi.org/10.1155/2023/8682054 |
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| _version_ | 1850159972050010112 |
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| author | Prasenjit Banerjee Asis Kumar Chattopadhyay Soumita Modak |
| author_facet | Prasenjit Banerjee Asis Kumar Chattopadhyay Soumita Modak |
| author_sort | Prasenjit Banerjee |
| collection | DOAJ |
| description | Data analysis for a sample of celestial bodies generally is preceded by the completeness test in order to verify whether the sample objects are proper representatives of the corresponding part of the universe. A data set following a multivariate, continuous, uniform distribution is said to be “complete in space.” This paper introduces a new approach to check for this completeness for any astronomical data set under a multivariate setup. Our proposed procedure, using the multiple tests of hypotheses based on nonparametric statistics, and consequently, combining their p values, outperforms others from the literature. |
| format | Article |
| id | doaj-art-b20aa4173f634cb4a363027bf613db0c |
| institution | OA Journals |
| issn | 1687-7977 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Astronomy |
| spelling | doaj-art-b20aa4173f634cb4a363027bf613db0c2025-08-20T02:23:18ZengWileyAdvances in Astronomy1687-79772023-01-01202310.1155/2023/8682054A New Approach to Astronomical Data Analysis Based on Multiple VariablesPrasenjit Banerjee0Asis Kumar Chattopadhyay1Soumita Modak2Department of StatisticsDepartment of StatisticsFaculty of StatisticsData analysis for a sample of celestial bodies generally is preceded by the completeness test in order to verify whether the sample objects are proper representatives of the corresponding part of the universe. A data set following a multivariate, continuous, uniform distribution is said to be “complete in space.” This paper introduces a new approach to check for this completeness for any astronomical data set under a multivariate setup. Our proposed procedure, using the multiple tests of hypotheses based on nonparametric statistics, and consequently, combining their p values, outperforms others from the literature.http://dx.doi.org/10.1155/2023/8682054 |
| spellingShingle | Prasenjit Banerjee Asis Kumar Chattopadhyay Soumita Modak A New Approach to Astronomical Data Analysis Based on Multiple Variables Advances in Astronomy |
| title | A New Approach to Astronomical Data Analysis Based on Multiple Variables |
| title_full | A New Approach to Astronomical Data Analysis Based on Multiple Variables |
| title_fullStr | A New Approach to Astronomical Data Analysis Based on Multiple Variables |
| title_full_unstemmed | A New Approach to Astronomical Data Analysis Based on Multiple Variables |
| title_short | A New Approach to Astronomical Data Analysis Based on Multiple Variables |
| title_sort | new approach to astronomical data analysis based on multiple variables |
| url | http://dx.doi.org/10.1155/2023/8682054 |
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