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A note on the delete-d jackknife variance estimators

Author

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  • Shi, Xiquan

Abstract

In this note, a new delete-d jackknife variance estimator Vj(d)* is proposed, which differs from the original delete-d jackknife estimator Vj(d). It is shown that Vj(d)* is less biased than Vj(d).

Suggested Citation

  • Shi, Xiquan, 1988. "A note on the delete-d jackknife variance estimators," Statistics & Probability Letters, Elsevier, vol. 6(5), pages 341-347, April.
    • Handle: RePEc:eee:stapro:v:6:y:1988:i:5:p:341-347
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    Cited by:

    1. Adrian O’Hagan & Thomas Brendan Murphy & Luca Scrucca & Isobel Claire Gormley, 2019. "Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap," Computational Statistics, Springer, vol. 34(4), pages 1779-1813, December.

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