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: 2026-10-27 20:33:28 UTC; root
Author: Erin Craig [aut, cre, cph] (ORCID:
        <https://orcid.org/0000-0002-4893-6671>), Rob Tibshirani [aut,
        cph]
Repository: https://cran.r-universe.dev
Date/Publication: 2026-10-27 18:49:47 UTC
RemoteUrl: https://github.com/cran/ptLasso
RemoteRef: HEAD
RemoteSha: 9261ccbc1b9aa0e87a5d65d45e98ef5ebffe974d