6. Statistics of Sparsely Sampled Curves

Abstract

We develop new statistical methods for analyzing sparsely sampled curves that vary in time. The typical dataset is differences in log gene expressions from case-control pairs for a large number of genes sampled relative to time of diagnosis. We focus on weak signals in the gene expression in many genes instead of strong signals in a few genes. The methods are based on moving windows in time, hypothesis testing, dimension reductions and randomization of the time to observa-tion.