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Distribution-free prediction intervals for the future current record statistics

机译:未来当前记录统计信息的无分布预测间隔

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Prediction of records plays an important role in many applications, such as, meteorology, hydrology, industrial stress testing and athletic events. In this paper, based on the observed current records of an iid sequence sample drawn from an arbitrary unknown distribution, we develop distribution-free prediction intervals as well as prediction upper and lower bounds for current records from another iid sequence. We also present sharp upper bounds for the expected lengths of the so obtained prediction intervals. Numerical computations of the coverage probabilities are presented for choosing the appropriate limits of the prediction intervals.
机译:记录的预测在许多应用中都起着重要作用,例如气象学,水文学,工业压力测试和体育赛事。在本文中,基于观察到的从任意未知分布中提取的iid序列样本的当前记录,我们开发了无分布的预测间隔以及对来自另一个iid序列的当前记录的预测上限和下限。对于如此获得的预测间隔的预期长度,我们也给出了清晰的上限。提出了覆盖概率的数值计算,用于选择预测间隔的适当限制。

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