How biased is the apparent error rate of a prediction rule?

Journal of the American Statistical Association

Volumn 81, Issue 394, 1986, Pages 461-470

  Efron, Bradley ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

AIC; Bootstrap methods; Cross validation; Generalized linear models; Logistic regression; Mallows s Cp

Indexed keywords

EID: 80053264999     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.1986.10478291     Document Type: Article

References (11)

1. Atkinson, A. C. (1980), “A Note on the Generalized Information Criterion for Choice of a Model,” Biometrika, 67, 413–418.
2. Craven, P., and Wahba, G. (1979), “Smoothing Noisy Data With Spline Functions: Estimating the Correct Degree of Smoothing by the Method of Generalized Cross-Validation,” Numerische Mathematik, 31, 377–403.
3. Efron, B. (1975), “The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis,” Journal of the American Statistical Association, 70, 892–898.
4. —— (1978a), “The Geometry of Exponential Families,” Annals of Statistics, 6, 362–376.
5. —— (1978b), “Regression and ANOVA With Zero-One Data: Measures of Residual Variation,” Journal of the American Statistical Association, 73, 113–121.
6. —— (1982), “Maximum Likelihood and Decision Theory,” Annals of Statistics, 10, 340–356.
7. —— (1983), “Estimating the Error Rate of a Prediction Rule: Improvements on Cross-Validation,” Journal of the American Statistical Association, 78, 316–331.
8. Golub, G., Heath, M., and Wahba, G. (1979), “Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter,” Technometrics, 21, 215–223.
9. p,” Technometrics, 15, 661–675.
10. McCullagh, P., and Nelder, J. (1983), Generalized Linear Models, New York: Chapman & Hall.
11. Stone, M. (1977), “An Asymptotic Equivalence of Choice of Model by Cross-Validation of Akaike’s Criterion,” Journal of the Royal Statistical Society, Ser. B, 39, 44–47.