Statistical Theory and the Computer

Bradley Efron and Gail Gong
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Bradley Efron: Stanford University
Gail Gong: Stanford University

A chapter in Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, 1981, pp 3-7 from Springer

Abstract: 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.

Keywords: Bias Correction; Prediction Rule; Bootstrap Estimate; Chronic Hepatitis Patient; Empirical Standard Deviation (search for similar items in EconPapers)
Date: 1981
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-9464-8_1

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DOI: 10.1007/978-1-4613-9464-8_1

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