1973
DOI: 10.1080/03610917308548273
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A New Goodness-of-Fit Test for the Two-Parameter Weibull or Extreme-Value Distribution with Unknown Parameters

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Cited by 15 publications
(14 citation statements)
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“…3 shows that the Weibull distribution is an appropriate failure time model for this component and the shape parameter β could be assumed constant. Moreover, the Mann's test [14] with the significance level of 0.05 conducted for each stress level also supports the Weibull distribution assumption. For other goodness-of-fit tests for the Weibull distribution, see Cabana and Quiroz [4], and Lockhart et al [12].…”
Section: Illustrative Examplementioning
confidence: 75%
“…3 shows that the Weibull distribution is an appropriate failure time model for this component and the shape parameter β could be assumed constant. Moreover, the Mann's test [14] with the significance level of 0.05 conducted for each stress level also supports the Weibull distribution assumption. For other goodness-of-fit tests for the Weibull distribution, see Cabana and Quiroz [4], and Lockhart et al [12].…”
Section: Illustrative Examplementioning
confidence: 75%
“…Манн [4] и другие исследователи [5 -7] разрабо-тали критерий согласия, предназначенный специаль-но для распределения Вейбулла. Применяется этот критерий для случая, когда под наблюдением нахо-дится не более 25 однотипных единиц оборудования (n≤25).…”
Section: определение параметров функции распределения времени срабатыunclassified
“…This is based on the fact, noted above, that when the underlying distribuiton is G(x), the H. are distributed approximately exponentially with -1 parameter unity and zero covariances. Mann et al [26) used another function of the V. to test this hypothesis. These will 1 be omitted here because it is believed the procedure will be discussed in the next paper in this series.…”
Section: Testing Of Hypothesesmentioning
confidence: 99%