Package: varGuid
Type: Package
Title: Variance-Guided Regression Improving Upon OLS and ANOVA
Version: 0.1.5
Date: 2026-06-18
Authors@R: c(
    person(given = "Sibei", family = "Liu", email = "sxl4188@miami.edu", role = "aut"),
    person(given = "Min", family = "Lu", email = "luminwin@gmail.com", role = c("aut", "cre")))
Author: Sibei Liu [aut],
  Min Lu [aut, cre]
Maintainer: Min Lu <luminwin@gmail.com>
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: glmnet, lmtest, sandwich
Description: Fits variance-guided linear regression models that provide an
    alternative to ordinary least squares (OLS) for general linear-model
    design matrices, including ANOVA-style encodings. The methods use an
    iteratively reweighted least squares estimator or an iteratively reweighted
    lasso estimator and implement the global linear mean-variance model from
    the associated 2026 Statistics in Medicine article <doi:10.1002/sim.70632>.
    Under the assumptions in that
    paper, the estimator matches the homoscedastic baseline in population
    predictive quasi-risk when variance is constant and improves on it when the
    variance depends on covariates. The grouping-based nonlinear prediction
    extension from Section 3 is available in the development version on GitHub.
Encoding: UTF-8
LazyData: true
URL: https://github.com/luminwin/varGuid
BugReports: https://github.com/luminwin/varGuid/issues
NeedsCompilation: no
Packaged: 2026-06-18 12:00:00 UTC; minlu
Repository: CRAN
Date/Publication: 2026-06-18 22:40:02 UTC
