# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "subsampling" in publications use:' type: software license: GPL-3.0-only title: 'subsampling: Optimal Subsampling Methods for Statistical Models' version: 0.1.1 doi: 10.32614/CRAN.package.subsampling abstract: Balancing computational and statistical efficiency, subsampling techniques offer a practical solution for handling large-scale data analysis. Subsampling methods enhance statistical modeling for massive datasets by efficiently drawing representative subsamples from full dataset based on tailored sampling probabilities. These probabilities are optimized for specific goals, such as minimizing the variance of coefficient estimates or reducing prediction error. authors: - family-names: Dong given-names: Qingkai email: qingkai.dong@uconn.edu - family-names: Yao given-names: Yaqiong - family-names: Wang given-names: Haiying repository: https://dqksnow.r-universe.dev repository-code: https://github.com/dqksnow/Subsampling commit: 10c1e6443d564cf53b6056f006f5ffd4d10e7c9f url: https://github.com/dqksnow/Subsampling date-released: '2024-11-02' contact: - family-names: Dong given-names: Qingkai email: qingkai.dong@uconn.edu