A Two-Parameter Ratio-Product-Ratio Type Exponential Estimator  for Finite Population Mean in Sample Surveys

Singh, Housila P.; Yadav, Anita

doi:10.18187/pjsor.v14i2.1905

Cited by 8 publications

(14 citation statements)

References 6 publications

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“…e proposed estimator is studied for the separate and combined effects of NR and ME. A simulation study shows that the proposed estimator is far better than the existing estimators of Grover and Kaur [24], Ekpenyong and Enang [26], Singh and Pal [29], and Gupta and Yadav [31].…”

Section: Discussionmentioning

confidence: 99%

“…is estimator proves its worth over Gupta and Shabbir [27] and Singh and Solanki [28] estimators. Singh and Pal [29] propose an exponential ratio type estimator as t sp � y(X/x)exp(X − x/X + x). Study shows that t sp performs efficiently than the usual unbiased estimator, classical ratio estimator, Kadilar and Cingi [30], and Bahl and Tuteja [25] estimator.…”

Section: Some Existing Estimatorsmentioning

confidence: 99%

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Assessing the Effect of Nonresponse and Measurement Error Using a Novel Class of Efficient Estimators

Tiwari

Bhougal

Kumar

et al. 2022

Journal of Mathematics

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The purpose of any statistical analysis is to uncover the trend using real situations and provide an accurate model for future policies. In order to fulfill this aim, it is important to collect and use the data carefully and minimize the possibility of various types of errors. Nonresponse (NR) and measurement error (ME) are the two major types of nonsampling error that occur in almost every survey. We propose an estimator of the population mean and study its efficacy in the combined and separate effects of NR and ME. Some existing estimators are also considered for comparison. A simulation study was performed to see its efficiency numerically.

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Section: Discussionmentioning

confidence: 99%

Section: Some Existing Estimatorsmentioning

confidence: 99%

Assessing the Effect of Nonresponse and Measurement Error Using a Novel Class of Efficient Estimators

Tiwari

Bhougal

Kumar

et al. 2022

Journal of Mathematics

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show abstract

“…We propose a new imputation method that was inspired by Singh and Horn [18] and Singh and Pal [9], employing a modified auxiliary variable as a chain ratio exponential and new constants 1 2…”

Section: Proposed Imputation Methods and Corresponding Estimationmentioning

confidence: 99%

“…In fact, estimating the population mean is a fundamental statistical tool of data analysis in general research. Furthermore, auxiliary information can improve the precision of the estimator, so several authors including Bahl and Tuteja [8], Singh and Pal [9], Jaroengeratikun and Lawson [10] defined the estimator of population mean using auxiliary information under a simple random sample without replacement scheme (SRSWOR).…”

Section: 5mentioning

confidence: 99%

Estimating the Mean of PM2.5 with Missing Data in the Area Around Electricity Generating Authority of Thailand Using the Improved Compromised Imputation Method

Dachochaiporn

Chodjuntug

2023

Curr. Appl. Sci. Technol.

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Particulate matter with an aerodynamic diameter of less than 2.5 m or , is one of the air pollutants that has been found to be at unsafe levels for a number of years in Thailand, leading to public health concerns. In order to lessen the detrimental effects of air pollution, monitoring and analysis of concentration are crucial. Following the study of data from the Pollution Control Department Report in the area around the Electricity Generating Authority of Thailand in January 2019, it was found that there was data missing in the information. It is well-known that missing data can reduce the accuracy of data analysis. To solve the missing data problem, this paper proposes an improved method of compromised imputation and a corresponding resultant estimator to deal with estimating the mean of concentrations in the area. The bias and mean square error of the estimator obtained from the proposed method were derived. The conditions which favor the performance of our estimator over other estimators obtained from the mean, ratio, and compromised imputation methods were obtained using mean square error to apply in the area. The mean of concentrations in this case using the proposed estimator was equal to 47.13 g/m3, indicating that it did not exceed unsafe levels (<50 g/m3) under certain conditions. In order to support more accurate data analysis that will lead to effective management of air pollution problems in the future, this research proposes a new method that is more effective than the existing methods under missing data problem.

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“…Srivenkataramana (1980) and Bandyopadhyay (1980) have advocated the use of product method of estimation in case of positive correlation using simple transformation which induce the negative correlation even if the correlation between the two variables   x y, is positive. Later many other authors have worked on the ratio and product methods of estimations such as Kadilar and Cingi (2004), Grover and Kaur (2011), Singh et al (2015), Singh and Yadav (2018), Pal et al (2018Pal et al ( , 2019…”

Section: Introductionmentioning

confidence: 99%

A General Class of Dual to Ratio Estimator

Singh

Nigam²

2020

Pak.j.stat.oper.res.

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In this paper we have considered the problem of estimating the population mean using auxiliary information in sample surveys. A class of dual to ratio estimators has been defined. Exact expressions for bias and mean squared error of the suggested class of dual to ratio estimator have been obtained. In particular, properties of some members of the proposed class of dual to ratio estimators have been discussed. It has been shown that the proposed class of estimators is more efficient than the sample mean, ratio estimator, dual to ratio estimator and some members of the suggested class of estimators in some realistic conditions. Some numerical illustrations are given in support of the present study.

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A Two-Parameter Ratio-Product-Ratio Type Exponential Estimator for Finite Population Mean in Sample Surveys

Cited by 8 publications

References 6 publications

Assessing the Effect of Nonresponse and Measurement Error Using a Novel Class of Efficient Estimators

Assessing the Effect of Nonresponse and Measurement Error Using a Novel Class of Efficient Estimators

Estimating the Mean of PM2.5 with Missing Data in the Area Around Electricity Generating Authority of Thailand Using the Improved Compromised Imputation Method

A General Class of Dual to Ratio Estimator

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