A note on calibration weightings for stratified double sampling with equal probability

Clement, Etebong P.

doi:10.1080/03610926.2017.1342836

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…Multi-parametric calibration weightings is the formulation of calibration constraints with respect to a given distance measure to obtain expression of calibration weights using information from two or more parameters of the same supplementary variable. Work in this aspect include among others, Tracy et al (2003), Koyuncu and Kadilar (2016), Clement (2018), Clement (2020) and Clement and Etukudoh (2023).…”

Section: International Journal Of Statistical Sciences Vol 24(1) 2024mentioning

confidence: 99%

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On the Use of Inverse Exponentiation to Improve the Efficiency of Calibration Estimators in Stratified Double Sampling

Clement,

Enang

2024

Int. J. of Stat. Sci.

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This study introduces the concept of inverse exponentiation in formulating calibration weights in stratified double sampling and proposes a more improved calibration estimator based on Koyuncu and Kadilar (2014) calibration estimator. The variance of the proposed logarithmic calibration estimator has been derived under large sample approximation. Calibration asymptotic optimum estimator and its approximate variance estimator are derived for the proposed logarithmic calibration estimator. Results of empirical study showed that the proposed logarithmic calibration estimator performs better than the Koyuncu and Kadilar (2014) calibration estimator with appreciable gains in efficiency. Also, simulation study for the comparison of the proposed logarithmic estimator with a Global estimator [Generalized Regression (GREG) estimator ] proved the robustness of the proposed logarithmic calibration estimator and by extension the efficacy of inverse exponentiation in calibration weightings. Analysis and evaluation are presented. International Journal of Statistical Sciences, Vol.24(1), March, 2024, pp 91-102

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Section: International Journal Of Statistical Sciences Vol 24(1) 2024mentioning

confidence: 99%

“…This section derives the estimator of variance for the Koyuncu and Kadilar (2014) calibration estimator. Thus, expressing (7) in the relative error terms gives…”

Section: Theoretical Variance Estimationmentioning

confidence: 99%

On the Use of Inverse Exponentiation to Improve the Efficiency of Calibration Estimators in Stratified Double Sampling

Clement,

Enang

2024

Int. J. of Stat. Sci.

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“…To judge the relative performances of the suggested estimator over the regression estimator, data set from [24] given in table 1 was considered.…”

Section: Empirical Studymentioning

confidence: 99%

Ratio-product estimator in stratified double sampling based on coefficient of skewness of the auxiliary variable

Clement¹

2021

Int. J. Stat. Appl. Math.

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In this paper, a ratio-product estimator for estimating the population mean of the study variable based on the population coefficient of skewness of the auxiliary variable is suggested in stratified double sampling. Asymptotic optimum estimator and its approximate bias and variance expressions are derived. Properties of the suggested estimator are studied with some known existing estimators identified as special members of this class of estimators. Analytical and numerical investigations showed that the suggested estimator is more efficient than the conventional regression estimator of mean in stratified double sampling and existing estimators of its class in stratified double sampling. Analysis and evaluation are presented.

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“…Koyuncu and Kadilar [4] provided novel calibration estimators under stratified random sampling. Climate [5] proposed a calibration estimator for estimating the population mean utilizing calibration weights under stratified double sampling. Ozgul [6] provided a calibration approach alternative to existing calibration estimators for estimating Y using an auxiliary variable in stratified sampling.…”

Section: Introductionmentioning

confidence: 99%

Robust calibration for estimating the population mean using stratified random sampling

Zaman

Bulut

2023

Scientia Iranica

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Estimating the population mean is of prime concern in many studies, and calibrations are popular choices. A robust calibration estimator estimates the mean using the minimum covariance determinant (MCD) and the minimum volume ellipsoid (MVE) estimations under stratified random sampling.Efficiency comparisons have been made between the robust calibration estimator and classical calibration estimator. Simulations and empirical results show that the proposed robust calibration estimator has a lower mean square error than the calibration estimators. When the relative efficiency and computation times are considered together, it is seen that the proposed robust calibration estimators based on MCD estimates are more efficient.

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A note on calibration weightings for stratified double sampling with equal probability

Cited by 6 publications

References 10 publications

On the Use of Inverse Exponentiation to Improve the Efficiency of Calibration Estimators in Stratified Double Sampling

On the Use of Inverse Exponentiation to Improve the Efficiency of Calibration Estimators in Stratified Double Sampling

Ratio-product estimator in stratified double sampling based on coefficient of skewness of the auxiliary variable

Robust calibration for estimating the population mean using stratified random sampling

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