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Biometrika 1992 79(3):577-582; doi:10.1093/biomet/79.3.577
© 1992 by Biometrika Trust
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Properties of estimators of the finite population distribution function

R. L. CHAMBERS1, ALAN H. DORFMAN2 and PETER HALL3

1Statistics Research Section, Australian National University G.P.O. Box 4, Canberra, A.C.T. 2601, Australia
2Department of Mathematics, Tulane University New Orleans, Louisiana 70118, U.S.A.
3Statistics Research Section, Australian National University G.P.O. Box 4, Canberra, A.C.T. 2601, Australia

Two leading estimators of the finite population distribution function are studied. Their large-sample mean squared errors are compared, under a given model. Neither estimator is universally better; circumstances are identified where the model-based estimator would do poorly, despite employing the correct model.

Key Words: Asymptotic bias • Asymptotic mean squared error • Auxiliary information • Consistency • Linear model • Regression model • Sample survey design


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