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On Testing Autocorrelation in Metrology Data Under Indeterminacy
MAPAN ( IF 1 ) Pub Date : 2021-03-05 , DOI: 10.1007/s12647-021-00429-1
Muhammad Aslam

The existing Durbin–Watson (DW) test is applied when all observations are determined and certain. The Durbin–Watson test under neutrosophic statistics is presented in this test. The proposed neutrosophic Durbin–Watson test can be applied to test either autocorrelation exists in error terms when neutrosophy is presented in the data. The proposed test statistic is introduced and applied to the data that are taken from the metrology. From the analysis, it is concluded that the proposed test is quite effective to apply to the metrology data in the presence of indeterminacy. In addition, it is found that the proposed test is efficient than the existing DW test under classical statistics.



中文翻译:

在不确定性下测试计量数据中的自相关

确定并确定所有观测值后,将应用现有的Durbin-Watson(DW)检验。在中智统计下的Durbin–Watson检验在该检验中提出。提议的中智Durbin–Watson检验可以用于检验中智学在数据中存在的自相关是否存在误差。引入了建议的测试统计量,并将其应用于从度量中获取的数据。从分析中可以得出结论,在存在不确定性的情况下,所提出的测试非常有效地应用于计量数据。另外,发现在经典统计下,提出的测试比现有的DW测试有效。

更新日期:2021-03-05
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