交通大学、清华大学统计学研究所专题演讲 题　目：Prediction Intervals for General Balanced Linear Random Models 主讲人：林彩玉教授(逢甲大学应数系) 时　间：98年4月17日(星期五)上午10:40-11:30 (上午10:20-10:40茶会於交大统计所429室举行) 地　点：交大综合一馆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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