Forecasting Records
研究了如何根据某项体育赛事的历史纪录来预测未来纪录，将纪录视为随机过程，通过扩展次序统计理论推导出任意两个时期的纪录的联合分布和协方差，并用广义最小二乘法进行参数估计和预测。
We address the problem of forecasting the future records for an athletic event on the basis of the observed past records in that event. The records are viewed as realizations of a random process. The bivariate distribution and covariance of the record in any two periods is derived by a simple extension of the theory of order statistics. In the special case of a uniform, normal, or extreme-value parent, minimum-variance-linear-unbiased (MVLU) estimates of the parameters and “best” forecasts of future records may be obtained by generalized least squares. As an illustration, forecasts of the world record in six major running events are calculated for a 15-year period.