Time series data analysis under indeterminacy
Abstract The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals or imprecise. In this paper, we will introduce a semi-average method under neutro...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-08-01
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| Series: | Journal of Big Data |
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| Online Access: | https://doi.org/10.1186/s40537-023-00806-4 |
| _version_ | 1797559101083877376 |
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| author | Muhammad Aslam |
| author_facet | Muhammad Aslam |
| author_sort | Muhammad Aslam |
| collection | DOAJ |
| description | Abstract The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals or imprecise. In this paper, we will introduce a semi-average method under neutrosophic statistics to measure the trend in imprecise or interval data. The application of the proposed semi-average method will be given using the wind speed data. The efficiency of the proposed semi-average method under neutrosophic statistics will be given over the semi-average method under classical statistics in terms of information and adequacy. |
| first_indexed | 2024-03-10T17:40:50Z |
| format | Article |
| id | doaj.art-717cd694b5f349c6bb40b6fe71930cc8 |
| institution | Directory Open Access Journal |
| issn | 2196-1115 |
| language | English |
| last_indexed | 2024-03-10T17:40:50Z |
| publishDate | 2023-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj.art-717cd694b5f349c6bb40b6fe71930cc82023-11-20T09:42:29ZengSpringerOpenJournal of Big Data2196-11152023-08-0110111110.1186/s40537-023-00806-4Time series data analysis under indeterminacyMuhammad Aslam0Department of Statistics, Faculty of Science, King Abdulaziz UniversityAbstract The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals or imprecise. In this paper, we will introduce a semi-average method under neutrosophic statistics to measure the trend in imprecise or interval data. The application of the proposed semi-average method will be given using the wind speed data. The efficiency of the proposed semi-average method under neutrosophic statistics will be given over the semi-average method under classical statistics in terms of information and adequacy.https://doi.org/10.1186/s40537-023-00806-4Semi average methodTrendImprecise dataClassical statisticsForecasting |
| spellingShingle | Muhammad Aslam Time series data analysis under indeterminacy Journal of Big Data Semi average method Trend Imprecise data Classical statistics Forecasting |
| title | Time series data analysis under indeterminacy |
| title_full | Time series data analysis under indeterminacy |
| title_fullStr | Time series data analysis under indeterminacy |
| title_full_unstemmed | Time series data analysis under indeterminacy |
| title_short | Time series data analysis under indeterminacy |
| title_sort | time series data analysis under indeterminacy |
| topic | Semi average method Trend Imprecise data Classical statistics Forecasting |
| url | https://doi.org/10.1186/s40537-023-00806-4 |
| work_keys_str_mv | AT muhammadaslam timeseriesdataanalysisunderindeterminacy |