We explore the evaluation (ranking) of point forecasts by a “stochastic loss distance” (SLD) criterion, under which we prefer forecasts with loss distributions F(L(e)) “close” to the unit step function at 0. We show that, surprisingly, ranking by SLD corresponds to ranking by expected loss.

Gene microarray technology is often used to compare the expression of thousand of genes in two different cell lines. Typically, one does not expect measurable changes in transcription amounts for a large number of genes; furthermore, the noise level of array experiments is rather high in...