Asymptotic properties of a generalized regression-type predictor of a finite population variance in probability sampling

A system of predictors for estimating a finite population variance is defined and shown to be asymptotically design-unbiased (ADU) and asymptotically design-consistent (ADC) under probability sampling. An asymptotic mean squared error (MSE) of a generalized regression-type predictor, generated from...

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Veröffentlicht in:	Canadian journal of statistics 1996-09, Vol.24 (3), p.373-384
Hauptverfasser:	Shah, D. N., Patel, P. A.
Format:	Artikel
Sprache:	eng
Schlagworte:	62J05 AMS 1991 subject classifications: 62D05 AMS 1991 subject classifications: 62D05, 62J05 asymptotic design unbiasedness and consistency Asymptotic properties Estimators generalized regression-type predictor mean squared error minimum expected variance Modeling Population estimates Population mean Population parameters Probabilities Regression analysis regression model Sampling studies Statistical variance Unequal probability sampling
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