交通大學、清華大學統計學研究所專題演講 題　目：Prediction Intervals for General Balanced Linear Random Models 主講人：林彩玉教授(逢甲大學應數系) 時　間：98年4月17日(星期五)上午10:40-11:30 (上午10:20-10:40茶會於交大統計所429室舉行) 地　點：交大綜合一館427室 Abstract The main interest of prediction intervals lies in the results of a future sample from a previously sampled population. In this article, we develop procedures for the prediction intervals which contain all of a fixed number of future observations for general balanced linear random models. Two methods based on the concept of a generalized pivotal quantity (GPQ) and one based on ANOVA estimators are presented. A simulation study using the balanced one-way random model is conducted to evaluate the proposed methods. It is shown that one of the two GPQ-based and the ANOVA-based methods are computationally more efficient and they also successfully maintain the simulated coverage probabilities close to the nominal confidence level. Hence, they are recommended for practical use. Furthermore, one example is given to illustrate the applicability of the recommended methods. --

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