Consistency of jackknife variance estimators jun
- 1 January 1991
- journal article
- research article
- Published by Taylor & Francis in Statistics
- Vol. 22 (1) , 49-57
- https://doi.org/10.1080/02331889108802282
Abstract
A class of delete-d jackknife estimators of the asymptotic variances of point estimators are shown to be consistent when d, the number of observations removed from the original sample, is a fraction of n and the point estimators are generated from a sta¬tistical functional which possesses a weak differentiability property. The computation of the delete-∧ jackknife estimators is almost as easy as the traditional delete-1 jackknife estimator. The results are applied to problems in robust M-estimationKeywords
This publication has 7 references indexed in Scilit:
- A General Theory for Jackknife Variance EstimationThe Annals of Statistics, 1989
- Jackknifing Differentiable Statistical FunctionalsJournal of the Royal Statistical Society Series B: Statistical Methodology, 1985
- Uniqueness and Frechet Differentiability of Functional Solutions to Maximum Likelihood Type EquationsThe Annals of Statistics, 1983
- Jackknifing L-Statistics with Smooth Weight FunctionsJournal of the American Statistical Association, 1982
- Approximation Theorems of Mathematical StatisticsPublished by Wiley ,1980
- A Differential for $L$-StatisticsThe Annals of Statistics, 1979
- The Influence Curve and Its Role in Robust EstimationJournal of the American Statistical Association, 1974