# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "NeEDS4BigData" in publications use:' type: software license: MIT title: 'NeEDS4BigData: New Experimental Design Based Subsampling Methods for Big Data' version: 1.0.1 doi: 10.32614/CRAN.package.NeEDS4BigData abstract: Subsampling methods for big data under different models and assumptions. Starting with linear regression and leading to Generalised Linear Models, softmax regression, and quantile regression. Specifically, the model-robust subsampling method proposed in Mahendran, A., Thompson, H., and McGree, J. M. (2023) , where multiple models can describe the big data, and the subsampling framework for potentially misspecified Generalised Linear Models in Mahendran, A., Thompson, H., and McGree, J. M. (2025) . authors: - family-names: Mahendran given-names: Amalan email: amalan0595@gmail.com orcid: https://orcid.org/0000-0002-0643-9052 repository: https://amalan-constat.r-universe.dev repository-code: https://github.com/Amalan-ConStat/NeEDS4BigData commit: b6d978ea8650f48c86db84056abd76641c1d27e6 url: https://amalan-constat.github.io/NeEDS4BigData/index.html date-released: '2025-10-18' contact: - family-names: Mahendran given-names: Amalan email: amalan0595@gmail.com orcid: https://orcid.org/0000-0002-0643-9052