You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
William R. Schucany and Simon J. Sheather
Vol. 76, No. 2 (Jun., 1989), pp. 393-398
Stable URL: http://www.jstor.org/stable/2336674
Page Count: 6
You can always find the topics here!Topics: Standard error, Estimators, Statism, Arithmetic mean, Statistical variance, Consistent estimators, Confidence interval, Estimation methods, Statistics, Maximum likelihood estimation
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Sufficient conditions are given for the consistency of the jackknife variance estimator for R-estimators of location in the one- and two-sample problems. In particular, the jackknife is shown to produce strongly consistent estimates of the variance of the Hodges-Lehmann estimator. An efficient algorithm for computing the variance estimator is presented. For the two sample sizes considered in this paper, calculations for the jackknife estimator of the variance of the Hodges-Lehmann estimator are about 50 times as fast as the bootstrap variance estimator with B = 100. Some Monte Carlo evidence of the small-sample efficiency of this jackknife variance estimator is reported. Extensions of the results to R-estimators in the linear model context are discussed.
Biometrika © 1989 Biometrika Trust