A class of estimators of population mean using auxiliary information in the presence of non-response

Dubey, Vyas; Uprety, Minal

doi:10.3233/mas-2008-3205

Cited by 4 publications

(2 citation statements)

References 1 publication

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“…Cochran [2], Rao [3,4], Khare and Srivastava [5][6][7], Okafor and Lee [8], Tabasum and Khan [9,10], Sodipo and Obisesan [11], Singh and Kumar [12][13][14], and Singh et al [15] have studied the problem of nonresponse under double sampling using the auxiliary information. Dubey and Uprety [16] used second raw moments for efficient estimation of population means in the presence of nonresponse. Al-Hossain and Khan [17] used maximum and minimum values of population for improved estimation of population mean.…”

Section: Introductionmentioning

confidence: 99%

A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

Khan

Shabbir

Hussain

et al. 2014

Journal of Applied Mathematics

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This paper presents new classes of estimators in estimating the finite population mean under double sampling in the presence of nonresponse when using information on fractional raw moments. The expressions for mean square error of the proposed classes of estimators are derived up to the first degree of approximation. It is shown that a proposed class of estimators performs better than the usual mean estimator, ratio type estimators, and Singh and Kumar (2009) estimator. An empirical study is carried out to demonstrate the performance of a proposed class of estimators.where = / for = 1, 2; 1 = ∑ 1 =1 / 1 and 2 = ∑ =1 / .

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Section: Introductionmentioning

confidence: 99%

A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

Khan

Shabbir

Hussain

et al. 2014

Journal of Applied Mathematics

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“…The problem of estimating finite population mean has been discussed by various authors such as Sisodia and Dwivedi [16], Pandey and Dubey [6], Upadhyaya and Singh [21], Singh and Tailor [13], Singh and Vishwakarma [11], Tailor and Tailor [17], Dubey and Uprety [3], Singh and Vishwakarma [12], Grover and Kaur [4], Tailor et al [18] and Upadhyaya et al [19]. But very little literature is found regarding use of auxiliary information in the estimation of ratio of two population means.…”

Section: Introductionmentioning

confidence: 99%

Improved ratio-cum-product type exponential estimators for ratio of two population means in sample surveys

Tailor

Lone

2014

MAS

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This paper considers the problem of estimation of ratio of two population means. In this paper, a ratio-cum-product type exponential estimator is suggested using auxiliary information in the form of known population mean of two auxiliary variates. Almost unbiased estimator for ratio of two population means is obtained using bias subtraction and random group methods. An optimum estimator is also achieved in random group method. Expressions for bias and mean squared error are obtained up to the first degree of approximation. Conditions under which the suggested estimator is more efficient than usual estimator, Singh [14] estimators, Singh [15] estimator and Rawal [8] estimators are obtained. A generalized version of the suggested estimator is also given with its properties. An empirical study has been carried out to demonstrate the performance of the suggested estimators.

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Two new estimators of finite population variance under random non-response: An application

Mittal¹,

Kumar²

2023

MAS

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In this paper, an attempt has been made to study the estimation of finite population variance in simple random sampling without replacement (SRSWOR) in presence of non-response by proposing two estimators. The two estimators (dual to ratio and ratio cum dual to ratio type) have been proposed on the basis of availability and non-availability of auxiliary information. The properties such as bias and mean square error of the proposed estimators have also been studied up to first order of approximation. The proposed estimators are compared with some existing estimators and are also mutually compared. An empirical study, based on both vegetable crop data and simulated data, has been performed to find out the best estimator. It has been seen that out of the two proposed estimators, the ratio cum dual to ratio type estimator performed better than dual to ratio estimator.

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A class of estimators of population mean using auxiliary information in the presence of non-response

Cited by 4 publications

References 1 publication

A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

Improved ratio-cum-product type exponential estimators for ratio of two population means in sample surveys

Two new estimators of finite population variance under random non-response: An application

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