savvyPR: Savvy Parity Regression Model Estimation with 'savvyPR'

Implements the Savvy Parity Regression 'savvyPR' methodology for multivariate linear regression analysis. The package solves an optimization problem that balances the contribution of each predictor variable to ensure estimation stability in the presence of multicollinearity. It supports two distinct parameterization methods, a Budget-based approach that allocates a fixed loss contribution to each predictor, and a Target-based approach (t-tuning) that utilizes a relative elasticity weight for the response variable. The package provides comprehensive tools for model estimation, risk distribution analysis, and parameter tuning via cross-validation (PR1, PR2, and PR3 model types) to optimize predictive accuracy. Methods are based on Asimit, Chen, Ichim and Millossovich (2026) <https://openaccess.city.ac.uk/id/eprint/35005/>.

Version:	0.1.0
Depends:	R (≥ 3.6.0)
Imports:	glmnet, Matrix, stats, nleqslv, ggplot2, gridExtra
Suggests:	MASS, knitr, rmarkdown, testthat (≥ 3.0.0), covr
Published:	2026-03-17
DOI:	10.32614/CRAN.package.savvyPR
Author:	Ziwei Chen [aut, cre], Vali Asimit [aut], Pietro Millossovich [aut]
Maintainer:	Ziwei Chen <Ziwei.Chen.3 at citystgeorges.ac.uk>
BugReports:	https://github.com/ziwei-chenchen/savvyPR/issues
License:	GPL (≥ 3)
URL:	https://ziwei-chenchen.github.io/savvyPR/
NeedsCompilation:	no
Materials:	README
CRAN checks:	savvyPR results

Documentation:

Reference manual:	savvyPR.html , savvyPR.pdf
Vignettes:	Savvy Parity Regression Model Estimation with 'savvyPR' (source, R code)

Downloads:

Package source:	savvyPR_0.1.0.tar.gz
Windows binaries:	r-devel: savvyPR_0.1.0.zip, r-release: savvyPR_0.1.0.zip, r-oldrel: savvyPR_0.1.0.zip
macOS binaries:	r-release (arm64): savvyPR_0.1.0.tgz, r-oldrel (arm64): savvyPR_0.1.0.tgz, r-release (x86_64): savvyPR_0.1.0.tgz, r-oldrel (x86_64): savvyPR_0.1.0.tgz

Linking:

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