Description: Simple git client for R based on 'libgit2' <https://libgit2.org> with
support for SSH and HTTPS remotes. All functions in 'gert' use basic R data
types (such as vectors and data-frames) for their arguments and return values.
User credentials are shared with command line 'git' through the git-credential
store and ssh keys stored on disk or ssh-agent.
SystemRequirements: libgit2 (>= 1.0): libgit2-devel (rpm) or

Imports: askpass, credentials (>= 1.2.1), openssl (>= 2.0.3),

Title: Generalized Structured Component Analysis (GSCA)
Author: Heungsun Hwang, Sunmee Kim, Sungyoung Lee, Taesung Park
Description: Fit a variety of component-based structural equation models.

Title: R Client for GESIS Data Catalogue (DBK)
Authors@R: person("Eric", "Persson", email = "expersso5@gmail.com", role = c("aut", "cre"))
Description: Provides programmatic access to the GESIS - Leibniz-Institute for
the Social Sciences Data Catalogue/Datenbestandkatalog (DBK), which
maintains a large repository of data sets related to the social sciences.

See <http://www.gesis.org> for more information.

Title: Reproducible Data Retrieval from the GESIS Data Archive
person("Frederick", "Solt", email = "frederick-solt@uiowa.edu", role = c("aut", "cre", "cph")))
Description: Reproducible, programmatic retrieval of datasets from the
GESIS Data Archive.  The GESIS Data Archive <https://search.gesis.org>
makes available thousands of invaluable datasets, but researchers using
these datasets are caught in a bind.  The archive's terms and conditions
bar dissemination of downloaded datasets to third parties, but to ensure
that one's work can be reproduced, assessed, and built upon by others, one
must provide access to the raw data one has employed.  The 'gesisdata'
package cuts this knot by providing registered users with programmatic,
reproducible access to GESIS datasets from within 'R'.
Imports: magrittr, rio, RSelenium (>= 1.7.1), stringr, dplyr, tools,

Title: Hierarchical GxE Interactions in a Regularized Regression Model
Description: The method focuses on a single environmental exposure and induces
a main-effect-before-interaction hierarchical structure for the joint selection of interaction terms
in a regularized regression model. For details see Zemlianskaia et al. (2021) <arxiv:2103.13510>.
Imports: Rcpp (>= 1.0.3), Matrix, bigmemory, methods
Suggests: glmnet, testthat, knitr, rmarkdown, ggplot2
LinkingTo: Rcpp, RcppEigen, RcppThread, BH, bigmemory
Packaged: 2021-06-04 19:16:34 UTC; nataliazemlianskaia