Statistical validation of genetic models

Abstract

Various aspects of statistical validation of genetic models are reviewed. Possible ways of decomposing additive genetic variance over time and ways of comparing predictions at different times are suggested. Ways of circumventing difficulties because of selection are suggested. The uses of cross-validatory techniques are illustrated. Techniques introduced to validate multiple country evaluation are discussed. The analogy of multiple country evaluation with sequential comparison of predictors is shown.