Abstract
Everyone here knows that the modern computer has profoundly changed statistical practice. The effect upon statistical theory is less obvious. Typical data analyses still rely, in the main, upon ideas developed fifty years ago. Inevitably though, new technical capabilities inspire new ideas. Efron, 1979B, describes a variety of current theoretical topics which depend upon the existence of cheap and fast computation: the jackknife, the bootstrap, cross-validation, robust estimation, the EM algorithm, and Cox’s likelihood function for censored data.
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References
Cox, D. R. (1972). “Regression Models and Life Tables (with discussion)”, Journal of the Royal Statistical Society, Series B, 34, 187–220.
Efron, B. (1979A). “Bootstrap Methods: Another Look at the Jackknife”, Annals of Statistics, 7, 1–26.
Efron, B. (1979B). “Computers and the Theory of Statistics: Unthinkable”, SIAM Review, 21, 460–480.
Efron, B. (1980A). “Censored Data and the Bootstrap”, Technical Report No. 53, Department of Statistics, Stanford University. (To appear in Journal of the American statistical Association.)
Efron, B. (1980B). “Nonparametric Estimates of Standard Error: The Jackknife, the Bootstrap, and Other Methods”, Technical Report No. 56. Department of Statistics, Stanford University. (To appear in Biometrika.)
Efron, B. (1980C). “The Jackknife, the Bootstrap, and Other Resampling Plans”, Technical Report No. 63, Department of Statistics, Stanford University.
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© 1981 Springer-Verlag New York Inc.
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Efron, B., Gong, G. (1981). Statistical Theory and the Computer. In: Eddy, W.F. (eds) Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9464-8_1
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DOI: https://doi.org/10.1007/978-1-4613-9464-8_1
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