SplitKnockoff

Split Knockoff is a data adaptive variable selection framework for controlling the (directional) false discovery rate (FDR) in structural sparsity, where variable selection on linear transformation of parameters is of concern. This proposed scheme relaxes the linear subspace constraint to its neighborhood, often known as variable splitting in optimization. Simulation experiments can be reproduced following the Vignette. We include data (both .mat and .csv format) and application with our method of Alzheimer's Disease study in this package. 'Split Knockoffs' is first defined in Cao et al. (2021) .