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savvyPR
View on CRAN: Click
here
Download and install savvyPR package within the R console
Install from CRAN:
install.packages("savvyPR")
Install from Github:
library("remotes")
install_github("cran/savvyPR") Install by package version:
library("remotes")
install_version("savvyPR", "0.1.0") Attach the package and use:
library("savvyPR")
Maintained by
Ziwei Chen
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-17
Latest Update: 2026-03-17
Description:
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/>.
How to cite:
Ziwei Chen (2026). savvyPR: Savvy Parity Regression Model Estimation with 'savvyPR'. R package version 0.1.0, https://cran.r-project.org/web/packages/savvyPR. Accessed 13 Sep. 2026.
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