# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "risdr" in publications use:' type: software license: GPL-3.0-or-later title: 'risdr: Regularised and Information-Theoretic Sufficient Dimension Reduction' version: 0.4.0 doi: 10.32614/CRAN.package.risdr identifiers: - type: doi value: 10.32614/CRAN.package.risdr abstract: Implements covariance-stabilised sufficient dimension reduction for continuous responses, with an additional sparse engine for continuous, categorical, and right-censored survival responses and information-theoretic structural dimension selection. Supported methods include sliced inverse regression, sliced average variance estimation, directional regression, and principal Hessian directions. Sample, ridge, Oracle Approximating Shrinkage, Ledoit-Wolf, and Maximum Entropy Covariance (MEC) estimators are provided alongside prediction, resampling, simulation, and diagnostic utilities. The sufficient dimension reduction methods build on Li (1991) , Li (1992) , and Li and Wang (2007) . Covariance shrinkage follows Olorede and Yahya (2019) , Ledoit and Wolf (2004) and Chen et al. (2010) . authors: - family-names: Olorede given-names: Kabir email: kabirolorede@gmail.com preferred-citation: type: manual title: 'risdr: Regularised and Information-Theoretic Sufficient Dimension Reduction' authors: - family-names: Olorede given-names: Kabir Opeyemi year: '2026' doi: 10.32614/CRAN.package.risdr notes: R package version 0.4.0 url: https://CRAN.R-project.org/package=risdr repository: https://ilovemaths.r-universe.dev repository-code: https://github.com/ilovemaths/risdr commit: 9add706529ec156d1570ee3390c09db303c9e06a url: https://ilovemaths.github.io/risdr/ date-released: '2026-10-12' contact: - family-names: Olorede given-names: Kabir email: kabirolorede@gmail.com references: - type: generic title: A New Covariance Estimator for Sufficient Dimension Reduction in High-Dimensional and Undersized Sample Problems authors: - family-names: Olorede given-names: Kabir Opeyemi - family-names: Yahya given-names: Waheed Babatunde year: '2019' notes: arXiv:1909.13017 [stat.ME] doi: 10.48550/arXiv.1909.13017 url: https://arxiv.org/abs/1909.13017