# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "dwmmlRidge" in publications use:' type: software license: MIT title: 'dwmmlRidge: Dynamically Weighted Modified Maximum Likelihood (DWMML) Ridge Regression' version: 0.1.1 doi: 10.32614/CRAN.package.dwmmlRidge abstract: Implements the dynamically weighted modified maximum likelihood ridge (DWMMLR) regression estimator, a robust and multicollinearity-aware linear regression estimator that combines the DWMML3 weighting procedure of Sazak (2019) with ridge penalization to address both outlier sensitivity and variance inflation due to multicollinearity. The ridge parameter is selected automatically using the approach implemented in the 'ridgregextra' package (Karadag, Sazak, and Aydin, 2023) , described further in Karadag, Sazak, and Aydin (2026) , which targets a variance inflation factor (VIF) close to but not below 1, removing the need for manual tuning. Returns comprehensive outputs (coefficients, fitted values, residuals, mean squared error (MSE), standard errors, R-squared, and adjusted R-squared) through a simple x/y interface. authors: - family-names: Karadag given-names: Filiz email: filiz.karadag@ege.edu.tr orcid: https://orcid.org/0000-0002-0116-7772 - family-names: Sazak given-names: Hakan Savas email: hakan.savas.sazak@ege.edu.tr orcid: https://orcid.org/0000-0001-6123-1214 - family-names: Aydin given-names: Olgun email: olgun.aydin@pg.edu.pl orcid: https://orcid.org/0000-0002-7090-0931 repository: https://filizkrdg.r-universe.dev repository-code: https://github.com/filizkrdg/dwmmlRidge commit: 075f96db4eaedd3f3d84b8a98f8e85871b2e0a0e url: https://github.com/filizkrdg/dwmmlRidge date-released: '2026-06-22' contact: - family-names: Karadag given-names: Filiz email: filiz.karadag@ege.edu.tr orcid: https://orcid.org/0000-0002-0116-7772