Generalized exponential chain ratio estimators under stratified two-phase random sampling

Sanaullah, Aamir; Ali, Humera Ameer; Noor‐ul‐Amin, Muhammad; Hanif, Muhammad

doi:10.1016/j.amc.2013.10.088

Cited by 36 publications

(18 citation statements)

References 13 publications

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“…The use of a transformed auxiliary variable provides more efficient estimators of population variance; see, for example, References [6][7][8][9][10][11].…”

Section: Methodsmentioning

confidence: 99%

On Efficient Estimation of Process Variability

2019

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Variability or dispersion plays an important role in any process and provides insight into the spread of data from some central point, usually the mean. A process with less spread is preferred over a process in which values differ greatly from the mean. Various methods are available to estimate the process dispersion by using information on the variable of interest. Certain additional variables provide good insight to estimate the process dispersion. In this paper, we propose an efficient method for the estimation of process variability by using the exponential method. The properties of the proposed method were studied. We conducted simulation and empirical studies to compare the proposed method with some existing methods of estimation of variability. The results of the numerical study show that our proposed method is better than the other methods used in the study.

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“…The use of a transformed auxiliary variable provides more efficient estimators of population variance; see, for example, References [6][7][8][9][10][11].…”

Section: Methodsmentioning

confidence: 99%

On Efficient Estimation of Process Variability

2019

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“…Observe that optimum choices of the constants 01 ,  and 2  are based on some parameters whose values may be from the prior surveys or may be presumed through the experience drawn in due course of time, for case in point see, Horvitz and Thompson [25], Sanaullah et al [26], Asghar et al [27], and Sanaullah et al [28]. In many real life situations, it may not be possible to guess these values through experience or prior surveys, so it is better to replace these values with the estimates drawn from a pilot surveys for case in point see Koyuncu and Kadilar [29] and Jabeen et al [30].…”

Section: Table 2 Class Of Estimators For Two Auxiliary Variablesmentioning

confidence: 99%

Estimation of Mean of a Sensitive Quantitative Variable in Complex Survey: Improved Estimator and Scrambled Randomized Response Model

Koyuncu

Saleem²,

Sanaullah³

et al. 2019

Gazi University Journal of Science

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Highlights• This paper introduces a new Scrambled Randomized Response model. • A simulation study is done to compare the efficiency of the proposed model. • The results showed that the proposed model performs better than existing model. Article Info AbstractWith the intention to control a true swapping between the efficiency and the privacy protection this paper introduces a scrambled randomized response (SRR) model to be alternative of Saha's scrambling mechanism. The basic initiative is to provide an assortment of the additive, the subtractive and the multiplicative models. The simulation and the empirical studies are provided for various sample sizes to compare the efficiency of the proposed model. The results obtained from simulation showed that the proposed model performs better than Pollock and Bek's additive model. Also, the proposed generalized estimator of mean has been studied using a new SRR model presented in this article and shown that the proposed estimator and its class of estimators are more efficient than existing estimators. It is also shown that gain in efficiency is more when the proposed SRR model is used. The efficiency of the proposed class of estimators over existing estimators using both models is also provided using real data and with a simulation study.

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“…Singh, Joarder and Tracy (2001) extended their idea to the situation of median estimation in two-phase sampling. The importance of double sampling and improvements on the estimation of population mean can also be seen in several publications by Vishwakarma and Kumar (2015), Vishwakarma and Gangele (2014), Vishwakarma and Singh (2011), Amin et al (2016), and Sanaullah et al (2014). However, none of these papers deal with the situation of making use of estimator of median of the auxiliary variable at the estimation stage of population mean of the study variable in twophase sampling.…”

Section: Introductionmentioning

confidence: 99%

A New Estimator of Mean Using Double Sampling

Vadlamudi

Sedory

Singh

2017

Statistics in Transition New Series

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In this paper, we consider the problem of estimation of population mean of a study variable by making use of first-phase sample mean and first-phase sample median of the auxiliary variable at the estimation stage. The proposed new estimator of the population mean is compared to the sample mean estimator, ratio estimator and the difference type estimator for the fixed cost of the survey by using the concept of two-phase sampling. The magnitude of the relative efficiency of the proposed new estimator has been investigated through simulation study.

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Generalized exponential chain ratio estimators under stratified two-phase random sampling

Cited by 36 publications

References 13 publications

On Efficient Estimation of Process Variability

On Efficient Estimation of Process Variability

Estimation of Mean of a Sensitive Quantitative Variable in Complex Survey: Improved Estimator and Scrambled Randomized Response Model

A New Estimator of Mean Using Double Sampling

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