An Efficient Class of Chain Estimators of Population Variance under Sub-Sampling Scheme

Jhajj, H. S.; Sharma, Manoj K.; Grover, Lovleen Kumar

doi:10.14490/jjss.35.273

Cited by 19 publications

(9 citation statements)

References 7 publications

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“…In light of the above shortcomings, several authors have studied to improve the existing classical ratio and product estimators to increase efficiency and also give better options in decision making. [17], [19], [20], [15], [1], [21], [8], [9], [10], [18], [2], [3], [16], [7] and [6] are amongst authors who have contributed in one way or the other to the modification of the classical ratio estimator for the population mean of the study variable under simple random sampling without replacement (SRSWOR) scheme with extensions to other sampling techniques. This study is another attempt to propose an alternative estimator for the population mean using a combination of necessary scalars which is expected to have small-er relative bias and compare favourably with the linear regression estimator.…”

Section: Background Of Studymentioning

confidence: 99%

A modified class of exponential-type estimator of population-mean in simple random sampling

Enang

Uket

Ekpenyong

2017

IJASP

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The problem of obtaining better ratio estimators of the population means are dominating in survey sampling. This paper provides a modified class of exponential type estimators using combinations of some existing estimators. Expressions for the bias and Mean Square Error (MSE) with the optimality conditions for this class of estimators have been established. Both analytical and numerical comparison with some existing estimators shows better performances from members of the proposed class.

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Section: Background Of Studymentioning

confidence: 99%

A modified class of exponential-type estimator of population-mean in simple random sampling

Enang

Uket

Ekpenyong

2017

IJASP

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“…If these parameters are unknown, then one can use the estimated values from the sample (see Srivastava and Jhajj, 1983;Jhajj et al, 2005;Koyuncu and Kadilar, 2009). …”

Section: Proposed Estimator In Stratified Random Samplingmentioning

confidence: 99%

On Estimating Finite Population Mean in Simple and Stratified Random Sampling

Shabbir

Gupta

2010

Communications in Statistics - Theory and Methods

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In this article, we propose an exponential ratio type estimator for estimating the finite population mean in simple and stratified random sampling. The properties of the proposed estimator are obtained and comparison is made with some of the existing estimators. The proposed estimator is found to perform better than the usual mean, ratio, exponential ratio, traditional regression and Pandy (1980) estimators in simple and stratified random sampling. We use six data sets for simple random sampling case and two data sets for stratified random sampling case to compare the performances of all of the estimators considered here.

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“…Isaki (1983) introduced the traditional ratio and regression estimator for population variance. Some related work in this direction is also due to Jhajj, Sharma & Grover (2005), Kadilar & Cingi (2006), Gupta & Shabbir (2008), Bansal, Javed & Khanna (2011), Singh, Chauhan, Swan & Smarandache (2011), Upadhyaya, Singh, Chatterjee & Yadav (2011), Subramani & Kumarapandiyan (2012, Nayak & Sahoo (2012) and Yadav & Kadilar (2013.…”

Section: Introductionmentioning

confidence: 99%

A Note on Generalized Exponential Type Estimator for Population Variance in Survey Sampling

Shabbir¹,

Gupta²

2015

Rev. colomb. estad.

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Recently a new generalized estimator for population variance using information on the auxiliary variable has been introduced by Asghar, Sanaullah & Hanif (2014). In that paper there was some inaccuracy in the bias and MSE expressions. In this paper, we provide the correct expressions for bias and MSE of the Asghar et al. (2014) estimator, up to the first order of approximation. We also propose a new generalized exponential type estimator for population variance which performs better than the existing estimators. Four data sets are used for numerical comparison of efficiencies.Key words: Auxiliary Variable, Bias, Efficiency, Mean Square Error, Variance. ResumenRecientemente, un nuevo estimador generalizado de varianza de la población utilizando información sobre la variable auxiliar ha sido introducida por Asghar et al. (2014). En ese documento había alguna inexactitud en las expresiones de sesgo y ECM. En este trabajo, proporcionamos las expresiones correctas de sesgo y ECM de Asghar et al. (2014) hasta el primer orden de aproximación. También proponemos un nuevo estimador tipo exponencial generalizado de la varianza de la población que se comporta mejor que los estimadores existentes. Cuatro conjuntos de datos se utilizan para la comparación numérica de la eficiencia.Palabras clave: error cuadrático medio, sesgo, variable auxiliar, varianza, eficiencia.a Professor.

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An Efficient Class of Chain Estimators of Population Variance under Sub-Sampling Scheme

Cited by 19 publications

References 7 publications

A modified class of exponential-type estimator of population-mean in simple random sampling

A modified class of exponential-type estimator of population-mean in simple random sampling

On Estimating Finite Population Mean in Simple and Stratified Random Sampling

A Note on Generalized Exponential Type Estimator for Population Variance in Survey Sampling

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