Standard errors and covariance matrices for smoothed rank estimators

Brown, B.M. & Wang, You-Gan (2005) Standard errors and covariance matrices for smoothed rank estimators. Biometrika, 92(1), pp. 149-158.

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Abstract

A 'pseudo-Bayesian' interpretation of standard errors yields a natural induced smoothing of statistical estimating functions. When applied to rank estimation, the lack of smoothness which prevents standard error estimation is remedied. Efficiency and robustness are preserved, while the smoothed estimation has excellent computational properties. In particular, convergence of the iterative equation for standard error is fast, and standard error calculation becomes asymptotically a one-step procedure. This property also extends to covariance matrix calculation for rank estimates in multi-parameter problems. Examples, and some simple explanations, are given.

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37 citations in Scopus
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35 citations in Web of Science®

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ID Code: 90521
Item Type: Journal Article
Refereed: Yes
Keywords: covariance estimator, estimating function, induced smoothing, kernel, estimator, linearisation, one step estimation, rank estimation, sandwich, formula, second-order convergence, standard error, Wilcoxon estimator, models
DOI: 10.1093/biomet/92.1.149
ISSN: 0006-3444
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 18 Nov 2015 01:13
Last Modified: 18 Nov 2015 01:13

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