Mean Squared Error of Estimation or Prediction Under a General Linear Model
研究了混合效应线性模型中固定和随机效应线性组合的预测问题，给出了用估计值替代未知参数后预测均方误差的精确或近似表达式，并考察了多种均方误差估计量。
Abstract The problem considered is that of predicting a linear combination of the fixed and random effects of a mixed-effects linear model. More generally, the problem considered is that of predicting an unobservable random variable from a set of observable random variables. The best linear-unbiased predictor depends on parameters which generally are unknown. Various exact or approximate expressions are given for the mean squared error (MSE) of the predictor obtained by replacing the unknown parameters with estimates. Several estimators of the MSE are investigated.