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Fast leave-one-out methods for inference, model selection, and diagnostic checking

Author

Listed:
  • Federico Belotti

    (University of Rome Tor Vergata)

  • Franco Peracchi

    (University of Rome Tor Vergata)

Abstract

In this article, we describe jackknife2, a new prefix command for jackknifing linear estimators. It takes full advantage of the available leave-one-out formula, thereby allowing for substantial reduction in computing time. Of special note is that jackknife2 allows the user to compute cross-validation and diagnos- tic measures that are currently not available after ivregress 2sls, xtreg, and xtivregress.

Suggested Citation

  • Federico Belotti & Franco Peracchi, 2020. "Fast leave-one-out methods for inference, model selection, and diagnostic checking," Stata Journal, StataCorp LP, vol. 20(4), pages 785-804, December.
    • Handle: RePEc:tsj:stataj:y:18:y:2018:i:4:p:785-804
    DOI: 10.1177/1536867X20976312
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    Cited by:

    1. Liu Zhu & Hongyan Zhang & Dan Cao & Yalan Xu & Lanzhi Li & Zilan Ning & Lei Zhu, 2022. "Drought Stress-Related Gene Identification in Rice by Random Walk with Restart on Multiplex Biological Networks," Agriculture, MDPI, vol. 13(1), pages 1-12, December.
    2. Annalivia Polselli, 2023. "Robust Inference in Panel Data Models: Some Effects of Heteroskedasticity and Leveraged Data in Small Samples," Papers 2312.17676, arXiv.org.
    3. Annalivia Polselli, 2023. "Influence Analysis with Panel Data," Papers 2312.05700, arXiv.org.

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