A note on iterative AK composite estimator for Current Population Survey

Yang Cheng; Bo Huang; Zhou Yu

doi:10.1080/10485252.2017.1303064

A note on iterative AK composite estimator for Current Population Survey

Yang Cheng, Bo Huang, Zhou Yu

School of Statistics

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

Abstract

In this article, we introduce the iterative AK composite estimator for the Current Population Survey. This estimator adopts the AK composite estimator as the initial value and further makes good use of the intrinsic composite scheme of the AK composite estimator. We derive the mean squared error (MSE) formula for the iterative composite estimator and describe how to select the optimal tuning coefficients by minimising the MSE. Finally, we examine the proposed method through a simulation study.

Original language	English
Pages (from-to)	381-390
Number of pages	10
Journal	Journal of Nonparametric Statistics
Volume	29
Issue number	2
DOIs	https://doi.org/10.1080/10485252.2017.1303064
State	Published - 3 Apr 2017

Keywords

AK composite estimator
Current Population Survey
iterative estimation
mean squared error

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10.1080/10485252.2017.1303064

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title = "A note on iterative AK composite estimator for Current Population Survey",

abstract = "In this article, we introduce the iterative AK composite estimator for the Current Population Survey. This estimator adopts the AK composite estimator as the initial value and further makes good use of the intrinsic composite scheme of the AK composite estimator. We derive the mean squared error (MSE) formula for the iterative composite estimator and describe how to select the optimal tuning coefficients by minimising the MSE. Finally, we examine the proposed method through a simulation study.",

keywords = "AK composite estimator, Current Population Survey, iterative estimation, mean squared error",

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AB - In this article, we introduce the iterative AK composite estimator for the Current Population Survey. This estimator adopts the AK composite estimator as the initial value and further makes good use of the intrinsic composite scheme of the AK composite estimator. We derive the mean squared error (MSE) formula for the iterative composite estimator and describe how to select the optimal tuning coefficients by minimising the MSE. Finally, we examine the proposed method through a simulation study.

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KW - iterative estimation

KW - mean squared error

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A note on iterative AK composite estimator for Current Population Survey

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Keywords

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