Estimating Events
研究基于样本估计具有正概率的事件，提出事件空间上的自然度量并定义最优估计量，推导了单变量指数模型分位数事件和多元正态模型椭球轮廓事件的最优估计量。
The problem of estimating an event, having positive probability content, based on a sample of $n$ observations is considered. A natural metric is shown to exist on the space of possible values for the event. This leads to the definition of optimal estimators. We derive optimal estimators for events which correspond to quantiles for the univariate exponential model. Further optimal estimators are derived for the events bounded by the ellipsoidal contours of the density function in the multivariate normal model.