Information-based optimal subdata selection for non-linear models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s00362-023-01430-3.pdf
Reference32 articles.
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2. Ai M, Yu J, Zhang H, Wang H (2021b) Optimal subsampling algorithms for big data regressions. Stat Sin 31:749–772
3. Atkinson AC, Fedorov VV (1975) The design of experiments for discriminating between two rival models. Biometrika 62:57–70
4. Cheng Q, Wang H, Yang M (2020) Information-based optimal subdata selection for big data logistic regression. J Stat Plan Inference 209:112–122
5. David HA, Hartley HO, Pearson ES (1954) The distribution of the ratio, in a single normal sample, of range to standard deviation. Biometrika 41:482–493
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