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Covariate and Newton–Raphson adjustments for a normal correlation coefficient when the variances are known

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  • Fosdick, Bailey K.
  • Perlman, Michael D.

Abstract

When the maximum likelihood estimator is computationally inconvenient, covariate and Newton–Raphson adjustment often provide algebraically explicit yet still asymptotically efficient estimators. The bivariate normal correlation coefficient with known variances is used to show that these methods may produce singularities that render the adjusted estimators unstable.

Suggested Citation

  • Fosdick, Bailey K. & Perlman, Michael D., 2013. "Covariate and Newton–Raphson adjustments for a normal correlation coefficient when the variances are known," Statistics & Probability Letters, Elsevier, vol. 83(12), pages 2627-2633.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:12:p:2627-2633
    DOI: 10.1016/j.spl.2013.08.007
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    References listed on IDEAS

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    1. Bailey K. Fosdick & Adrian E. Raftery, 2012. "Estimating the Correlation in Bivariate Normal Data With Known Variances and Small Sample Sizes," The American Statistician, Taylor & Francis Journals, vol. 66(1), pages 34-41, February.
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