Bradley Efron

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Bradley Efron (born May 1938) is a statistician best known for proposing the bootstrap resampling technique, which has had a major impact in the field of statistics and virtually every area of statistical application. The bootstrap was one of the first computer-intensive statistical techniques, replacing traditional algebraic derivations with data-based computer simulations. On May 29, 2007, he was awarded the National Medal of Science, the highest scientific honor by the United States, for his exceptional work in the field of Statistics (especially for his inventing of the bootstrapping methodology).[1]

Bradley Efron was born in St. Paul, Minnesota in May 1938, the son of Esther and Miles Efron. He attended the California Institute of Technology, graduating in Mathematics in 1960. He arrived at Stanford in fall of 1960, earning his Ph.D., under the direction of Rupert Miller and Herb Solomon, in the Department of Statistics.

He is currently a Professor of Statistics at Stanford. At Stanford he has been the Chair of the Department of Statistics, Associate Dean of Science, Chairman of the University Advisory Board, Chair of the Faculty Senate and Chair of the Undergraduate Program in Applied Mathematics.

Efron holds the Max H. Stein endowed chair as Professor of Humanities and Sciences at Stanford. He has won many honors, including a MacArthur Prize Fellowship, membership in the National Academy of Sciences and the American Academy of Arts and Sciences, fellowship in the Institute of Mathematical Statistics (IMS) and the American Statistical Association (ASA), the Wilks Medal, the Parzen Prize, and the Rao Prize, Fisher, Rietz and Wald lecturer.

He has made many important contributions to many areas of statistics. Efron's work has spanned both theoretical and applied topics, including empirical Bayes analysis (with Carl Morris), applications of differential geometry to statistical inference, the analysis of survival data, and inference for microarray gene expression data. He is the author of a classic monograph, The Jack-knife, the Bootstrap and Other Resampling Plans (1982) and has also co-authored (with R. Tibshirani) the text An Introduction to the Bootstrap (1994).


[edit] References

  • Bradley Efron (1979). "Bootstrap Methods: Another Look at the Jackknife". The Annals of Statistics 7 (1): 1–26. doi:10.1214/aos/1176344552. 
  • Bradley Efron; Robert Tibshirani (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.  [2]
  • Efron, B. (1979). Computer and the theory of statistics: thinking the unthinkable. SIAM Review.
  • Efron, B. (1981). Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods. Biometrika, 68, 589-599.
  • Efron, B. (1982). The jackknife, the bootstrap, and other resampling plans. Society of Industrial and Applied Mathematics CBMS-NSF Monographs, 38.
  • Diaconis, P. & Efron, B. (1983). Computer-intensive methods in statistics. Scientific American, May, 116-130.
  • Efron, B. (1983). Estimating the error rate of a prediction rule: improvement on cross-validation. J. Amer. Statist. Assoc.
  • Efron, B. (1985). Bootstrap confidence intervals for a class of parametric problems. Biometrika.
  • Efron, B. (1987). Better bootstrap confidence intervals. J. Amer. Statist. Assoc.
  • Efron, B. (1990). More efficient bootstrap computations. J. Amer. Statist. Assoc.
  • Efron, B. (1991). Regression precentiles using asymmetric squared error loss. Statistica sinica.
  • Efron, B. (1992). Jackknife-after-bootstrap standards errors and influence functions. in Journal of the Royal Statistical Society
  • Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York: Chapman & Hall, software.

[edit] External links


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