Estimation of finite population mean under PPS in presence of maximum and minimum values

Al-Marzouki, Sanaa; Chesneau, Christophe; Akhtar, Sohail; Nasir, Jamal Abdul; Ahmad, Sohaib; Hussain, Sardar; Jamal, Farrukh; Elgarhy, Mohammed; El-Morshedy, Mahmoud

doi:10.3934/math.2021318

Cited by 14 publications

(13 citation statements)

References 19 publications

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“…[ 4 ] for the first time, given in equation (1) :

Where

and

represents sample proportion for responses and lack of responses, while

and

represent the sample means of the variable of interest based on

and r units, respectively. The variance of the estimator

is given in equation [ 2 ]:

The usual ratio and product estimators for the population mean

are given in equation [ 3 , 4 ]:

and

…”

Section: Existing Estimatorsmentioning

confidence: 99%

“…There are several factors for a survey that affect the rate of non-response, including the nature of data collected, the publicity level, authorization of the investigating agency, respondents’ legal necessities, and the interval of the collector visit. The issue of non-response is more common and dominant in mail surveys as compared to surveys of special interviews [ [1] , [2] , [3] ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling

Hussain,

Zaman,

Khan

et al. 2024

Heliyon

View full text Add to dashboard Cite

“…[ 4 ] for the first time, given in equation (1) :

Where

and

represents sample proportion for responses and lack of responses, while

and

represent the sample means of the variable of interest based on

and r units, respectively. The variance of the estimator

is given in equation [ 2 ]:

The usual ratio and product estimators for the population mean

are given in equation [ 3 , 4 ]:

and

…”

Section: Existing Estimatorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling

Hussain,

Zaman,

Khan

et al. 2024

Heliyon

View full text Add to dashboard Cite

“…When there exists a positive or negative correlation between the study and the auxiliary variables, ratio and product estimators can improve the precision of estimates. By making use of the auxiliary information the researcher can explore these research ndings by looking in, Ahmad and Shabbir [1]; Kadilar and Cingi [2]; Grover and Kaur [3]; Haq et al [4]; and Al-Marzouki et al [5].…”

Section: Introductionmentioning

confidence: 99%

A Simulation Study: Population Distribution Function Estimation Using Dual Auxiliary Information under Stratified Sampling Scheme

Ahmad

Hussain

Zahid

et al. 2022

Mathematical Problems in Engineering

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In survey sampling, information on auxiliary variables related to the main variable is often available in many practical problems. Since the mid-twentieth century, researchers have taken a keen interest in the use of auxiliary information, due to its usefulness in estimation methods. In this article, our main objective is to discover the problem associated with estimation of the finite population distribution function, using the known auxiliary variable, which occurs as the sample distribution function and the rank of the auxiliary variable. A new family of the finite population distribution function estimators is proposed in the stratified sampling scheme. The mathematical equations for the bias and mean square error have been obtained for each proposed estimator, along with the eﬃciency conditions. Besides theoretical eﬃciency comparison, an empirical study has also been conducted to analyze the performance of estimators. A simulation study is also performed to observe the efficiency of the proposed estimators. The implementation of the proposed sampling scheme is illustrated by a practical example.

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“…A lot of work has been done on the estimation of the population mean. Some important references on the population mean estimation using auxiliary information include Diana [1], Kadilar and Cingi [2,3], Shabbir and Gupta [4], Shabbir and Gupta [5], Shabbir and Gupta [5], Haq and Shabbir [6], Aladag and Cingi [7], Singh and Khalid [8], Malik and Singh [9], Muneer et al [10], Shabbir and Gupta [11], Haq et al [12], Kaur et al [13], Ahmad and Shabbir [14], Singh and Khalid [15], Al-Marzouki et al [16], Ahmad et al [17], Ahmad et al [18], and Ahmad et al [19]. In these works, the authors have suggested improved ratio, product, and regression-type estimators for estimating the finite population mean.…”

Section: Introductionmentioning

confidence: 99%

A New Exponential Factor-Type Estimator for Population Distribution Function Using Dual Auxiliary Variables under Stratified Random Sampling

Iftikhar

Shi

Hussain

et al. 2022

Mathematical Problems in Engineering

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In this paper, we propose a generalized class of exponential-type estimators for estimating the finite population distribution function using dual auxiliary variables under stratified sampling. The biases and mean squared errors (MSEs) of the proposed class of estimators are derived up to the first order of approximation. The empirical and theoretical study of comparisons is discussed. Four populations are taken for the support of the theoretical findings. It is observed that the proposed class of estimators performs better as compared to all other considered estimators in stratified sampling.

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Estimation of finite population mean under PPS in presence of maximum and minimum values

Cited by 14 publications

References 19 publications

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling

A Simulation Study: Population Distribution Function Estimation Using Dual Auxiliary Information under Stratified Sampling Scheme

A New Exponential Factor-Type Estimator for Population Distribution Function Using Dual Auxiliary Variables under Stratified Random Sampling

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