Package: hierbase
Type: Package
Title: Enabling Hierarchical Multiple Testing
Version: 0.1.2
Authors@R: c(person("Claude", "Renaux", role = c("aut", "cre"), 
                    email = "renaux@stat.math.ethz.ch"), 
             person("Peter", "Bühlmann", role = c("ths")))
Description: Implementation of hierarchical inference based on Meinshausen (2008). 
    Hierarchical testing of variable importance. Biometrika, 95(2), 265-278 and 
    Renaux, Buzdugan, Kalisch, and Bühlmann, (2020). Hierarchical inference for 
    genome-wide association studies: a view on methodology with software. 
    Computational Statistics, 35(1), 1-40.  
    The R-package 'hierbase' offers tools to perform hierarchical inference 
    for one or multiple data sets based on ready-to-use (group) test functions
    or alternatively a user specified (group) test function. 
    The procedure is based on a hierarchical multiple testing 
    correction and controls the family-wise error rate (FWER). 
    The functions can easily be run in parallel. 
    Hierarchical inference can be applied to (low- or) high-dimensional 
    data sets to find significant groups or single variables (depending on 
    the signal strength and correlation structure) in a data-driven and 
    automated procedure. Possible applications can for example be found 
    in statistical genetics and statistical genomics.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: glmnet, hdi, methods, parallel, stats, SIHR
Suggests: knitr, MASS, testthat
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-11-08 10:32:19 UTC; renauxc
Author: Claude Renaux [aut, cre],
  Peter Bühlmann [ths]
Maintainer: Claude Renaux <renaux@stat.math.ethz.ch>
Repository: CRAN
Date/Publication: 2021-11-08 12:00:02 UTC
