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The BLUPs are not "best" when it comes to bootstrapping


  • Morris, Jeffrey S.


In the setting of mixed models, some researchers may construct a semiparametric bootstrap by sampling from the best linear unbiased predictor residuals. This paper demonstrates both mathematically and by simulation that such a bootstrap will consistently underestimate the variation in the data in finite samples.

Suggested Citation

  • Morris, Jeffrey S., 2002. "The BLUPs are not "best" when it comes to bootstrapping," Statistics & Probability Letters, Elsevier, vol. 56(4), pages 425-430, February.
  • Handle: RePEc:eee:stapro:v:56:y:2002:i:4:p:425-430

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    Cited by:

    1. Shang, Junfeng & Cavanaugh, Joseph E., 2008. "An assumption for the development of bootstrap variants of the Akaike information criterion in mixed models," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1422-1429, September.


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