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Assessing the Precision of a Jackknife Estimator  

Park, Dae-Su (Management Research Laboratory, KT)
Publication Information
Management Science and Financial Engineering / v.9, no.1, 2003 , pp. 4-10 More about this Journal
Abstract
We introduce a new estimator of the uncertainty of a jackknife estimate of standard error: the jack-knife-after-jackknife (JAJ). Using Monte Carlo simulation, we assess the accuracy of the JAJ in a variety of settings defined by statistic of interest, data distribution, and sample size. For comparison, we also assess the accuracy of the jackknife-after-bootstrap (JAB) estimate of the uncertainty of a bootstrap standard error. We conclude that the JAJ provides a useful new supplement to Tukey's jackknife, and the combination of jackknife and JAJ provides a useful alternative to the combination of bootstrap and JAB.
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1 Hill, C., Cartwright, P., and Arbaugh, J., 'Jackknifing the Bootstrap: Some Monte Carlo Evidence,' Communications in Statistics: Simulation and Computation 26 (1997), 125-139   DOI   ScienceOn
2 Liu,R., and Singh, K., Moving Blocks Jackknife and Bootstrap Capture Weak Dependence. In: LePage, R., Billard, L. (Eds.), Exploring the Limit of Bootstrap. Wiley, NY (1992), 225-248
3 Park, D., and Willemain, T., 'The Threshold Bootstrap and Threshold Jackknife,' Computational Statistics and Data Analysis 31 (1999), 187-202   DOI   ScienceOn
4 Tukey, J. (1958), 'Bias and Confidence Interval in Not Quite Large Samples (Abstract),' The Annals of Mathematical Statistics 29 (1958), 614   DOI   ScienceOn
5 Efron, B., and Tibshirani, R., An Introduction to the Bootstrap, Chapman & Hall. Inc.. New York 1993
6 Quenouille, M. (1949), 'Approximating Tests of Correlation in Time Series,' Journal of the Royal Statistical Society, Series B. 11 (1949), 68-84   DOI
7 Efron, B., and Tibshirani, R., 'Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Acyuracy,' Statistical Science 1 (1986), 54-77   DOI
8 Park, D., Kim, Y., Shin, K., and Willemain, T., 'Simulation Output Analysis Using the Threshold Bootstrap,' European Journal of Operational Research 134 (2001), 17-28   DOI   ScienceOn
9 Efron, B., 'Bootstrap Methods: Another Look at the Jackknife,' The Annals of Statistics 7 (1979), 1-26   DOI
10 Kunsch, H., 'The Jackknife and the Bootstrap for General Stationary Observations,' The Annals of Statistics 17 (1989), 1217-1241   DOI
11 Mosteller, F., and Tukey, J., Data Analysis and Regression: A Second Course in Statistics, Addison - Wesley, Reading, MA 1977
12 Efron, B., 'Jackknife-After-Bootstrap Standard Errors and Influence Functions (with discussion),' Journal of the Royal Statistical Society, Series B 54 (1992), 83-111