Approximate repeated-measures shrinkage

作者：Brentnall Adam R^*; Crowder Martin J; Hand David J

来源：Computational Statistics & Data Analysis, 2011, 55(2): 1150-1159.

DOI：10.1016/j.csda.2010.09.014

• Empirical Bayes
• Prediction
• Random effects

A general method is formalised for the problem of making predictions for a fixed group of individual units, following a sequence of repeated measures on each. A review of some related work is undertaken and, using some of its terminology, the approach might be described as approximate non-parametric empirical Bayes prediction. It is contended that the method may often produce predictions that are, in practice, comparable or not much worse than more sophisticated methods, but sometimes for a smaller computational cost. Two examples are used to demonstrate the approach, exploring the prediction of baseball averages and spatial-temporal rainfall. The method performs favourably in both examples in comparison with James-Stein, empirical Bayes and other predictions; it also provides a relatively simple and computationally feasible way of determining whether it is worth modelling between-individual variability.

• 出版日期2011-2-1