Measuring Performance of Ratio-Exponential-Log Type General Class of Estimators Using Two Auxiliary Variables

Shabbir, Javid; Ahmed, Shakeel; Sanaullah, Aamir; Onyango, Ronald

doi:10.1155/2021/5245621

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…By employing simple random sampling without replacement, 25 samples of size 5 are drawn from the population at regular intervals, and the results are compiled in Table 7. Each sample provides the usual mean estimators as ȳ and x, while the classical ratio estimator r , logarithmic estimator a , memory-type ratio estimator m r , and MTLE m a are computed using (1), ( 7), (12), and (18). Each sample is used to construct the EWMA statistic with η = 0.25.…”

Section: Numerical Studymentioning

confidence: 99%

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Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators

et al. 2023

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This article examines the issue of population mean estimation utilizing past and present data in the form of an exponentially weighted moving average (EWMA) statistic under simple random sampling (SRS). We suggest memory-type logarithmic estimators and derive their properties, such as mean-square error (MSE) and bias up to a first-order approximation. Using the EWMA statistic, the conventional and novel memory-type estimators are compared. Real and artificial populations are used as examples to illustrate the theoretical findings. According to the empirical findings, memory-type logarithmic estimators are superior to the conventional mean estimator, ratio estimator, product estimator, logarithmic-type estimator, and memory-type ratio and product estimators.

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Section: Numerical Studymentioning

confidence: 99%

“…Ref. [12] measured the effectiveness of the ratio-exponential-log type general class of estimators by utilizing two auxiliary variables. Logarithmic-type predictive estimators for population mean based on an RSS scheme were studied by [13].…”

Section: Introductionmentioning

confidence: 99%

Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators

et al. 2023

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“…It is very popular when auxiliary information is considered at the estimation phase, the ratio, product, regression, and exponential type estimators are mostly the preferred methods in di erent dimensions. Shabbir et al [1] examined the performance of ratio-exponential log type class of estimators using two auxiliary variables. Shahzad et al [2] introduced a novel family of variance estimators based on L-moments and calibration approach under strati ed simple random sampling (SSRS), whereas Shahzad et al [3] suggested L-Moments and calibration-based variance estimators under double SSRS and discussed an application of COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

Some Improved Classes of Estimators in Stratified Sampling Using Bivariate Auxiliary Information

Bhushan

Kumar

Onyango

et al. 2022

Journal of Probability and Statistics

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This manuscript considers some improved combined and separate classes of estimators of population mean using bivariate auxiliary information under stratified simple random sampling. The expressions of bias and mean square error of the proposed classes of estimators are determined to the first order of approximation. It is exhibited that under some particular conditions, the proposed classes of estimators dominate the existing prominent estimators. The theoretical findings are supported by a simulation study performed over a hypothetically generated population.

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Mean Estimation of a Sensitive Variable under Measurement Errors using Three-Stage RRT Model in Stratified Two-Phase Sampling

Onyango,

Oduor,

Odundo

2023

Pak.j.stat.oper.res.

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In the present study, the problem of mean estimation of a sensitive variable using three-stage RRT model under measurement errors is addressed. A generalized class of estimators is proposed using a mixture of auxiliary attribute and variable. Some members of the proposed generalized class of estimators are identified and studied. The bias and mean squared error (MSE) expressions for the proposed estimators are correctly derived up to first order Taylor's series of approximation. The proposed estimator's efficiency is investigated theoretically and numerically using real data. From the numerical study, the proposed estimators outperforms existing mean estimators. Furthermore, the efficiencies of the mean estimatorsâ€™ decreases as the sensitivity level of the survey question increases.

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Measuring Performance of Ratio-Exponential-Log Type General Class of Estimators Using Two Auxiliary Variables

Cited by 3 publications

References 15 publications

Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators

Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators

Some Improved Classes of Estimators in Stratified Sampling Using Bivariate Auxiliary Information

Mean Estimation of a Sensitive Variable under Measurement Errors using Three-Stage RRT Model in Stratified Two-Phase Sampling

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