A spacings-based prediction method for future upper record values is proposed as an alternative to maximum likelihood prediction. For an underlying family of distributions with continuous cumulative distribution functions, the general form of the predictor as a function of the estimator of the distributional parameters is established. A connection between this method and the maximum observed likelihood prediction procedure is shown. The maximum product of spacings predictor turns out to be useful to predict the next record value in contrast to likelihood-based procedures, which provide trivial predictors in this particular case. Moreover, examples are given for the exponential and the Pareto distributions, and a real data set is analyzed.

中文翻译：

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未来记录值的间距预测的最大乘积

提出了一种基于间距的未来上记录值预测方法作为最大似然预测的替代方法。对于具有连续累积分布函数的基本分布族，建立了作为分布参数估计量函数的预测变量的一般形式。显示了该方法与最大观测似然预测程序之间的联系。与基于似然的程序相比，间距预测器的最大乘积可用于预测下一个记录值，后者在这种特殊情况下提供微不足道的预测器。此外，给出了指数和帕累托分布的例子，并分析了一个真实的数据集。