An Efficient Class of Estimators for the Mean of a Finite Population in Two-Phase Sampling Using Multi-Auxiliary Variates

<abstract><p>This article deals with estimation of finite population mean using the auxiliary proportion under simple and two phase sampling scheme utilizing two auxiliary variables. Mathematical expressions for the mean squared errors of the proposed estimators are derived under first order of approximation. We compare the proposed class of estimators "theoretically and numerically" with the usual mean estimator of Naik and Gupta <sup>[<xref ref-type="bibr" rid="b1">1</xref>]</sup>. The theoretical as well as numerical findings support the superiority of our proposed class of estimator as compared to estimators available in literature.</p></abstract>

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A Class of Estimators for a Finite Population Mean Based on Multivariate Information and General two Phase Sampling

Calcutta Statistical Association Bulletin ◽

10.1177/0008068319950307 ◽

1995 ◽

Vol 45 (3-4) ◽

pp. 203-218 ◽

Cited By ~ 3

Author(s):

T. P. Tripathi ◽

M. S. Ahmed

Keyword(s):

Finite Population ◽

Population Data ◽

Two Phase ◽

Population Means ◽

Population Mean ◽

Phase Sampling ◽

Optimum Estimator ◽

Class Of Estimators ◽

Relative Gains ◽

Two Phase Sampling

A class of estimators for a finite population mean is presented for the situations where population means of some auxiliary variables are known while those of others are unknown. The results for general two phase sampling are indicated while the detailed discussion is made for the case when SRSWOR is used at both the phases. While several known estimators belong to the proposed clas~ some new estimators are identified as well. The optimum estimator in the proposed class is found to be better than the so-called chain ratio and regression estimators discu ssed by Chand (1975). Kiregyera (1984) and Mukerjee et al. (1987). The relative gains in efficiency of tho proposed optimum estimator over the others are obtained for a natural population data and found to be quite appreciable.

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A Study on the Chain Ratio-Type Estimator of Finite Population Variance

Journal of Probability and Statistics ◽

10.1155/2014/723982 ◽

2014 ◽

Vol 2014 ◽

pp. 1-5 ◽

Cited By ~ 3

Author(s):

Yunusa Olufadi ◽

Cem Kadilar

Keyword(s):

Finite Population ◽

Numerical Comparison ◽

Mean Square ◽

Auxiliary Variables ◽

Population Variance ◽

Two Phase ◽

First Order ◽

Phase Sampling ◽

The Mean ◽

Two Phase Sampling

We suggest an estimator using two auxiliary variables for the estimation of the unknown population variance. The bias and the mean square error of the proposed estimator are obtained to the first order of approximations. In addition, the problem is extended to two-phase sampling scheme. After theoretical comparisons, as an illustration, a numerical comparison is carried out to examine the performance of the suggested estimator with several estimators.

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A class of ratio-type estimators under two-phase sampling in the presence of auxilary variables

10.47302/jsr.2019530105 ◽

2019 ◽

Vol 53 (1) ◽

pp. 79-91

Author(s):

P. A. Patel ◽

F. H. Shah

Keyword(s):

Finite Population ◽

Natural Populations ◽

Small Scale ◽

Two Phase ◽

Population Mean ◽

First Order ◽

Special Cases ◽

Phase Sampling ◽

Class Of Estimators ◽

Two Phase Sampling

This paper deals with the estimation of population mean under two-phase sampling. Utilizing information on two-auxiliary variables, a class of estimators for estimating the finite population mean is proposed, and its properties, up to the first order of approximation, are studied. Various estimators are suggested as special cases of this class. The performance of the suggested estimators is compared with some contemporary estimators of population mean through numerical illustrations carried over existing datasets of some natural populations. Also, a small scale Monte Carlo simulation is carried out for the empirical comparison.

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