This monograph will provide an in-depth mathematical treatment of modern
multiple test procedures controlling the false discovery rate (FDR) and
related error measures, particularly addressing applications to fields
such as genetics, proteomics, neuroscience and general biology. The book
will also include a detailed description how to implement these methods
in practice. Moreover new developments focusing on non-standard
assumptions are also included, especially multiple tests for discrete
data. The book primarily addresses researchers and practitioners but
will also be beneficial for graduate students.