This note proposes an alternative implementation of the regression method which should be slightly faster than the principal components methods for estimating missing data. (RC)

Empirical Bayes methods are shown to provide a practical alternative to standard least squares methods in fitting high dimensional models to sparse data. An example concerning prediction bias in educational testing is presented as an illustration. (Author)