A new goodness of fit test in the presence of uncertain parameters - Aslam, Muhammad (Complex & intelligent systems, 2021)
The Weibull distribution has been widely used in the areas of quality and reliability. The Anderson–Darling test has been popularly used either the data in hand follow the Weibull distribution or not. The existing Anderson–Darling test under classical statistics is applied when all the observations in quality and reliability work are determined, précised, and exact. In the areas of reliability and quality, the data may indeterminate, in-interval and fuzzy. In this case, the existing Anderson–Darling test cannot be applied for testing the assumption of the Weibull distribution. In this paper, we present the Anderson–Darling test under neutrosophic statistics. We present the methodology to fit the neutrosophic Weibull distribution on the data. We discuss the testing procedure with the help of reliability data. We present the comparisons of the proposed test with the existing Anderson–Darling the goodness of fit test under classical statistics. From the comparison, it is concluded that the proposed test is more informative than the existing Anderson–Darling test under an indeterminate environment. In addition, the proposed test gives information about the measure of indeterminacy.