• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.27-34
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• 2004

The Horvitz-Thompson(H-T) estimator is less efficient than PPS estimators in some cases. We use the two-stage variable transformation in order to remove the drawbacks and increase the efficiency of H-T estimator. We transform the auxiliary variable to use the Midzuno-Sen sampling scheme at the first stage. And the next stage, we also transform the study variable to reduce the variance of H-T estimator using the inclusion probability obtained from the first transformation. We compare the efficiency between a suggested modified H-T estimator and PPS estimators.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.889-900
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• 2008

Child labour is a disturbing issue for any society. It is attempted here in this article to develop an estimator to assess the numerical strength of this menace in Lahore division. A Horvitz and Thompson (1952) type of estimator is developed where weights are calculated on the basis of poverty and illiteracy to increase the sampling efficiency. Different characteristic features of this estimator, like its unbiasedness, variance, probability distribution, confidence intervals are also developed for its study from different angles.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.57-69
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• 2007

Adaptive cluster sampling design is known as a sampling method for rare clustered population. Three modified adaptive cluster sampling designs are proposed. The adjusted Hansen-Hurwitz estimator and the Horvitz-Thompson estimator are considered. Efficiency issue of the proposed sampling designs is discussed in a Monte-Carlo simulation study.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.79-88
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• 2003

In this paper, we study the efficiency of the stratified estimator in related with the variance lower bound of Horvitz-Thompson estimator subject to the superpopulation model. Especially, we compare the variance lower bound of optimum allocation with that of power allocation subject to Dalenius-Hedges stratification.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.605-618
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• 2007

Adaptive sampling design is the selection procedure which depends on observed values of the variable of interest. It is the method which could be applied to the rare and unapproachable population. Adaptive cluster sampling strategies are more efficient than simple random sampling on equivalent sample size. Adaptive sampling with new estimators through the Rao-blackwell method have lower variance than Horvitz-Thompson (HT) and Hansen-Hurwitz (HH). Also, to determine suitable sample size, it was used expected sample and the method finding appropriate sample size by changing initial sample size were studied.