Truncated Midzuno-Sen sampling schemes for estimating distribution functions

Sarjinder Singh; Jong Min Kim; Hakjin Jang; Stephen Horn

doi:10.1080/03610918.2011.563006

Truncated Midzuno-Sen sampling schemes for estimating distribution functions

Sarjinder Singh, Jong Min Kim, Hakjin Jang, Stephen Horn

Statistics (Morris)

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

We consider a truncated Midzuno-Sen sampling scheme. The proposed method can be used to estimate the distribution function of a study variable assuming that the distribution function of an auxiliary variable is known. The ratio estimator for estimating the distribution function is shown to remain unbiased. We introduce the first- and second-order inclusion probabilities under the truncated Midzuno-Sen sampling scheme. Numerical examples are provided to support our theoretical results.

Original language	English (US)
Pages (from-to)	1096-1110
Number of pages	15
Journal	Communications in Statistics: Simulation and Computation
Volume	40
Issue number	7
DOIs	https://doi.org/10.1080/03610918.2011.563006
State	Published - Aug 2011

Keywords

Auxiliary information
Estimation of distribution function
Midzuno-Sen sampling scheme
Ratio type estimators

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10.1080/03610918.2011.563006

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AU - Horn, Stephen

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AB - We consider a truncated Midzuno-Sen sampling scheme. The proposed method can be used to estimate the distribution function of a study variable assuming that the distribution function of an auxiliary variable is known. The ratio estimator for estimating the distribution function is shown to remain unbiased. We introduce the first- and second-order inclusion probabilities under the truncated Midzuno-Sen sampling scheme. Numerical examples are provided to support our theoretical results.

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KW - Estimation of distribution function

KW - Midzuno-Sen sampling scheme

KW - Ratio type estimators

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JF - Communications in Statistics: Simulation and Computation

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ER -

Truncated Midzuno-Sen sampling schemes for estimating distribution functions

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Keywords

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