Package: studyStrap
Title: Study Strap and Multi-Study Learning Algorithms
Version: 1.0.0
Authors@R: c(person("Gabriel", "Loewinger", email = "gloewinger@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0755-8520")), 
		person("Giovanni", "Parmigiani", email = "gp@jimmy.harvard.edu", role = c("ths")), 
		person("Prasad", "Patil", email = "prpatil42@gmail.com", role = c("sad")),
		person("National Science Foundation", "Grant DMS1810829", role = c("fnd")),
		person("National Institutes of Health", "Grant T32 AI 007358", role = c("fnd")))
Description: Implements multi-study learning algorithms such as 
		merging, the study-specific ensemble (trained-on-observed-studies ensemble) the study strap, 
		the covariate-matched study strap, covariate-profile similarity weighting, and stacking weights. 
		Embedded within the 'caret' framework, this package allows for a wide range of 
		single-study learners (e.g., neural networks, lasso, random forests). 
		The package offers over 20 default similarity measures and allows for specification of custom 
		similarity measures for covariate-profile similarity weighting and an accept/reject step. 
		This implements methods described in Loewinger, Kishida, Patil, and Parmigiani. (2019)
		<doi:10.1101/856385>.
Maintainer: Gabriel Loewinger <gloewinger@gmail.com>
Depends: R (>= 3.1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: caret, tidyverse (>= 1.2.1), pls (>= 2.7-1), nnls(>= 1.4), CCA
        (>= 1.2), MatrixCorrelation (>= 0.9.2), dplyr (>= 0.8.2),
        tibble (>= 2.1.3)
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-10 17:54:15 UTC; gabeloewinger
Author: Gabriel Loewinger [aut, cre] (<https://orcid.org/0000-0002-0755-8520>),
  Giovanni Parmigiani [ths],
  Prasad Patil [sad],
  National Science Foundation Grant DMS1810829 [fnd],
  National Institutes of Health Grant T32 AI 007358 [fnd]
Repository: CRAN
Date/Publication: 2020-02-20 09:10:02 UTC
Built: R 4.6.0; ; 2026-04-25 14:00:01 UTC; unix
