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Optimal Prediction Intervals for Future Order Statistics from Extreme Value Distributions

机译:来自极值分布的未来订单统计的最佳预测间隔

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Prediction intervals for future order statistics are widely used for reliability problems and other related problems. The determination of these intervals has been extensively investigated. But the optimality property of these intervals has not been fully explored. In this paper we discuss this problem for extreme value distributions. Introducing a risk function to compare prediction intervals, the interval which minimizes it among the class of invariant prediction intervals is obtained. The technique used here for optimization of prediction intervals based on censored data emphasizes pivotal quantities relevant for obtaining ancillary statistics and factors. It allows one to solve the optimization problems in a simple way.
机译:未来订单统计的预测间隔被广泛用于可靠性问题和其他相关问题。这些间隔的确定已经过广泛研究。但这些间隔的最优性财产尚未完全探索。在本文中,我们讨论了极限分布的这个问题。引入危险功能以比较预测间隔,获得最小化不变预测间隔类中的间隔。这里使用的技术用于优化基于缩官数据的预测间隔,强调了与获得辅助统计和因素相关的枢转量。它允许以简单的方式解决优化问题。

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