Nonparametric estimation of the conditional mean function for additive models is investigated in cases where the observed data are dependent. We use an additive kernel estimator which is a sum of Nadaraya--Watson estimators. Under a strong mixing condition, the kernel estimator is shown to be...

An important problem in microarray experiments is the detection of genes that are differentially expressed in agiven mumber of classes. We consider a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be...