scholarly journals Efficient Class of Estimators for Finite Population Mean using Auxiliary Information in Two-Occasion Successive Sampling

2019 ◽  
Vol 17 (2) ◽  
Author(s):  
G. N. Singh ◽  
Mohd Khalid
Keyword(s):  
Linear Combination ◽  
Finite Population ◽  
Auxiliary Information ◽  
Successive Sampling ◽  
Sample Mean ◽  
Population Means ◽  
Population Mean ◽  
Practical Applications ◽  
Optimum Estimator ◽  
Class Of Estimators

In the case of sampling on two occasions, a class of estimators is considered which uses information on the first occasion as well as the second occasion in order to estimate the population means on the current (second) occasion. The usefulness of auxiliary information in enhancing the efficiency of this estimation is examined through the class of proposed estimators. Some properties of the class of estimators and a strategy of optimum replacement are discussed. The proposed class of estimators were empirically compared with the sample mean estimator in the case of no matching. The established optimum estimator, which is a linear combination of the means of the matched and unmatched portions of the sample at the current occasion, was empirically compared with the proposed class of estimators. Mutual comparisons of the proposed estimator were carried out. Suitable recommendations are made to the survey statistician for practical applications.

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

1995 ◽  
Vol 45 (3-4) ◽  
pp. 203-218 ◽  
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.

scholarly journals An Alternative Estimator for Estimating the Finite Population Mean Using Auxiliary Information in Sample Surveys

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Ramkrishna S. Solanki ◽  
Housila P. Singh ◽  
Anjana Rathour
Keyword(s):  
Finite Population ◽  
Auxiliary Information ◽  
Auxiliary Variable ◽  
Population Mean ◽  
Asymptotic Expressions ◽  
Variance Formula ◽  
Optimum Estimator ◽  
Class Of Estimators ◽  
Alternative Estimator ◽  
Usual Product

This paper suggests a class of estimators for estimating the finite population mean of the study variable using known population mean of the auxiliary variable . Asymptotic expressions of bias and variance of the suggested class of estimators have been obtained. Asymptotic optimum estimator (AOE) in the class is identified along with its variance formula. It has been shown that the proposed class of estimators is more efficient than usual unbiased, usual ratio, usual product, Bahl and Tuteja (1991), and Kadilar and Cingi (2003) estimators under some realistic conditions. An empirical study is carried out to judge the merits of suggested estimator over other competitors practically.

scholarly journals A General Class of Dual to Ratio Estimator

2020 ◽  
pp. 421-431
Author(s):  
Housila Prasad Singh ◽  
Pragati Nigam
Keyword(s):  
General Class ◽  
Mean Squared Error ◽  
Auxiliary Information ◽  
Ratio Estimator ◽  
Sample Surveys ◽  
Sample Mean ◽  
Population Mean ◽  
Squared Error ◽  
Class Of Estimators ◽  
Ratio Estimators

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.

Tuning design weights to deal with non-response in successive sampling

2021 ◽  
Vol 16 (2) ◽  
pp. 97-108
Author(s):  
Kumari Priyanka
Keyword(s):  
Natural Population ◽  
Simulation Study ◽  
Finite Population ◽  
Auxiliary Information ◽  
Population Level ◽  
Successive Sampling ◽  
Population Mean ◽  
Design Weights

The estimation of finite population mean at current occasion in two occasion successive sampling in presence of non-response is investigated using tuned jackknife estimators. Based on the availability of auxiliary information at population level (Info U) and sample level (Info s) and using tuned jackknife technique, estimators have been proposed. Estimator of variance of proposed estimators have also been discussed. Different cases of occurance of non-response have been explored. The estimators are mutually compared. The properties of these estimators are studied via simulation study using natural population.

scholarly journals An Improved Family of Estimators of Finite Population Mean Using Information on an Auxiliary Variable in Sample Surveys

2017 ◽  
Vol 13 (2) ◽  
pp. 77-108
Author(s):  
H. P. Singh ◽  
A. Yadav
Keyword(s):  
Mean Squared Error ◽  
Auxiliary Information ◽  
Auxiliary Variable ◽  
Sample Surveys ◽  
Sample Mean ◽  
Population Mean ◽  
Squared Error ◽  
Parameter Ratio ◽  
Large Sample Approximation ◽  
Class Of Estimators

Abstract In this paper we have suggested a family of estimators of the population mean using auxiliary information in sample surveys. The bias and mean squared error of the proposed class of estimators have been obtained under large sample approximation. We have derived the conditions for the parameters under which the proposed class of estimators has smaller mean squared error than the sample mean, ratio, product, regression estimator and the two parameter ratio-product-ratio estimators envisaged by Chami et al (2012). An empirical study is carried out to demonstrate the performance of the proposed class of estimators over other existing estimators.

scholarly journals A Class of Estimator for Population Mean Under SRS

2020 ◽  
Vol 2 (1) ◽  
pp. 9-26
Author(s):  
Syed Abdul Rehman ◽  
Mohammad Asif
Keyword(s):  
Mean Square Error ◽  
Auxiliary Information ◽  
Degree Of Approximation ◽  
Mean Square ◽  
Population Mean ◽  
Class Of Estimators ◽  
Efficiency Comparison

In this paper we propose a class of estimators for the estimation of finitepopulation mean using the auxiliary information when SRS scheme is used. Theexpressions for the Bias and mean square error (MSE) of the existing andsuggested class of estimators are derived up to first degree of approximation andthe efficiency comparison of suggested class of estimators is made with otherexisting estimators, using both theoretically and numerically based on realpopulation sets.

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