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Description

New Experimental Design Based Subsampling Methods for Big Data.

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) <doi:10.1007/s00362-023-01446-9>, 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) <doi:10.48550/arXiv.2510.05902>.
Metadata

Version

1.0.1

License

Unknown

Platforms (76)

    Darwin
    FreeBSD
    Genode
    GHCJS
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    MMIXware
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    OpenBSD
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