Functions to compute split generalized linear models. The approach fits
generalized linear models that split the covariates into groups. The
optimal split of the variables into groups and the regularized estimation
of the coefficients are performed by minimizing an objective function
that encourages sparsity within each group and diversity among them.

Functions to compute split generalized linear models. The approach fits
generalized linear models that split the covariates into groups. The
optimal split of the variables into groups and the regularized estimation
of the coefficients are performed by minimizing an objective function
that encourages sparsity within each group and diversity among them.
Example applications can be found in Christidis et al. (2021)
<arXiv:2102.08591>.

Haoxue Wang [aut, cre] (Development of the whole packages),
Yang Cao [aut] (Revison of this package),
Xinwei Sun [aut] (Original ideas about the package),
Yuan Yao [aut] (Testing for the package and management of the
development)
c(person("Haoxue", "Wang", role = c("aut","cre"),
comment="Development of the whole packages",
email="haoxwang@student.ethz.ch"),
person("Yang", "Cao", role = c("aut"),
comment="Revison of this package"),
person("Xinwei", "Sun", role = c("aut"),
comment="Original ideas about the package"),
person("Yuan", "Yao", role = c("aut"),
comment="Testing for the package and management of the development"))
A novel method for controlling the false discovery rate (FDR)
in structural sparsity setting. 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.
'Split Knockoffs' is defined in Cao et al. (2021) <arXiv:2103.16159>.
glmnet, MASS, latex2exp, RSpectra, ggplot2, Matrix, stats,
mvtnorm

A novel method for controlling the false discovery rate (FDR)
in structural sparsity setting. 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 defined in Cao et al. (2021) <arXiv:2103.16159>.