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小批量计量抽样方案的预测区间方法：正态过程的单次抽样AI 解读

A prediction-interval approach is used to derive variables sampling plans applicable to finite lots. A normally distributed process is assumed, and lots ranging in size from 5 to 70 are considered. The plans are such that, with high probability, accepted lots will have zero defects (defined in terms of one-sided specification limits). Further, tabulations provide information which is useful for selecting sample size for a specified combination of lot size and acceptable…

小批量计量抽样方案的预测区间方法：高斯过程下的一次抽样AI 解读

A prediction-interval approach is used to derive variables sampling plans applicable to finite lots. A normally distributed process is assumed, and lots ranging in size from 5 to 70 are considered. The plans are such that, with high probability, accepted lots will have zero defects (defined in terms of one-sided specification limits). Further, tabulations provide information which is useful for selecting sample size for a specified combination of lot size and acceptable…

可靠性与寿命数据的统计分析方法AI 解读

Methods for statistical analysis of reliability and life data , Methods for statistical analysis of reliability and life data , کتابخانه‌های دانشگاه کردستان

位置尺度族中次序统计量的最优与简化线性不变预测AI 解读

We observe the early failures of identical items simultaneously put under stress and use their failure times to predict later failure times in the same sample. Best linear invariant predictors and two simplified predictors are presented and their relative behaviour for some specific distributions is indicated in a table.

有限批量计量抽样方案的决策理论方法：指数与高斯过程的单次抽样AI 解读

A decision-theoretic approach is used to derive a variables sampling plan applicable to finite lots. A sampling distribution is derived for a general manufacturing process, and one-sided acceptance regions are determined for the particular cases in which the manufacturing process is described by either a normal distribution or an exponential distribution. Comparisons show that for a given risk level, a substantial savings in sample sizes can be effected over those required…

指数分布参数、预测区间与 Beta 百分位数的卡方近似AI 解读

The use of Patnaik's [28] chi-square approximation to the noncentral chi-square distribution and the Wilson-Hilferty [32] transformation of chi-square to approximate normality are explored as a simple, efficient means of finding k-order-statistic confidence bounds on parameters and reliability of the one- and two-parameter negative exponential distributions. An important implication of the results leads to obtaining simple closed-form approximations to percentiles of the…

指数分布参数、预测区间与贝塔分位数的卡方近似AI 解读

The use of Patnaik's [28] chi-square approximation to the noncentral chi-square distribution and the Wilson-Hilferty [32] transformation of chi-square to approximate normality are explored as a simple, efficient means of finding k-order-statistic confidence bounds on parameters and reliability of the one- and two-parameter negative exponential distributions. An important implication of the results leads to obtaining simple closed-form approximations to percentiles of the…

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