Symmetrized Data Aggregation

We develop a new class of distribution free multiple testing rules for false discovery rate (FDR) control under general dependence. A key element in our proposal is a symmetrized data aggregation (SDA) approach to incorporating the dependence structure via sample splitting, data screening and information pooling. The proposed SDA filter first constructs a sequence of ranking statistics that fulfill global symmetry properties, and then chooses a data driven threshold along the ranking to control the FDR. For more information, see the website below and the accompanying paper: Du et al. (2023), "False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation", . Some optional functionality uses the archived R packages ‘huge’ and ‘pfa’, which are not available from CRAN’s main repositories. Users who need this optional functionality can obtain them from the CRAN Archive as follows: ‘huge’ at < https://cran.r-project.org/src/contrib/Archive/huge/>; ‘pfa’ at < https://cran.r-project.org/src/contrib/Archive/pfa/>.