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On Testing Autocorrelation in Metrology Data Under Indeterminacy

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Abstract

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.

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Aslam, M. On Testing Autocorrelation in Metrology Data Under Indeterminacy. MAPAN 36, 515–519 (2021). https://doi.org/10.1007/s12647-021-00429-1

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