Package: ptLasso
Type: Package
Title: Pretraining the Lasso
Description: Implements lasso pretraining for generalized linear models for data with grouped observations; data without grouped observations, but with multinomial responses; data with multiple Gaussian responses; and data with repeated measurements over time.
 The method fits a lasso model to an initial dataset and then uses its support and coefficient values to guide model fitting for a related task, which can improve performance by leveraging larger datasets and preserve interpretability by identifying features which are generally shared, and which are task specific.
 See Craig et al. (2026) <doi:10.1093/jrsssb/qkaf050> for details.
 Model fitting in this package is done with cv.glmnet() from the 'glmnet' package, and syntax closely follows that of 'glmnet' (Friedman, Hastie and Tibshirani (2010) <doi:10.18637/jss.v033.i01>).
Version: 1.0.2
Authors@R: c(person("Erin", "Craig", role=c("aut", "cre", "cph"), email = "ercr@umich.edu", comment = c(ORCID = "0000-0002-4893-6671")),
	     person("Rob", "Tibshirani", role=c("aut", "cph")))
Maintainer: Erin Craig  <ercr@umich.edu>
License: GPL-2
Encoding: UTF-8
URL: https://erincr.github.io/ptLasso/,
        https://doi.org/10.1093/jrsssb/qkaf050
BugReports: https://github.com/erincr/ptLasso/issues
NeedsCompilation: yes
RoxygenNote: 7.3.3
Depends: ggplot2, glmnet, gridExtra, Matrix
Suggests: knitr, rmarkdown, rpart, survival, xgboost, sparsepca, MASS,
        testthat
VignetteBuilder: knitr
Language: en
Packaged: 2026-10-16 20:48:46 UTC; ercr
Author: Erin Craig [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-4893-6671>),
  Rob Tibshirani [aut, cph]
Repository: CRAN
Date/Publication: 2026-10-27 17:00:02 UTC
