scholarly journals Dual to Ratio and Product Type Exponential Estimators of Finite Population Mean in Double Sampling for Stratification

2017 ◽  
Vol 4 (5) ◽  
pp. 1-8
Author(s):  
Arpita Lakhre ◽  
Keyword(s):  
Finite Population ◽  
Product Type ◽  
Double Sampling ◽  
Population Mean ◽  
Double Sampling For Stratification

scholarly journals Ratio in Ratio Type Exponential Strategy for the Estimation of Population Mean

2021 ◽  
Author(s):  
Anurag Gupta ◽  
Rajesh Tailor
Keyword(s):  
Unbiased Estimator ◽  
Finite Population ◽  
Mean Squared Error ◽  
Double Sampling ◽  
Ratio Estimator ◽  
Population Mean ◽  
Squared Error ◽  
Double Sampling For Stratification

This paper is an attempt to develop an estimator for finite population mean. Motivated by Kiregyera (1984), a ratio in ratio type exponential strategy is developed for estimation of population mean in double sampling for stratification. To compare with relevant considered estimators, expressions for bias and mean squared error of the developed estimator have been derived. The developed estimator has been compared with usual unbiased estimator, Ige and Tripathi (1987), ratio estimator and ratio type exponential estimator given by Tailor et al (2014) theoretically as well as empirically.

scholarly journals Modified Exponential Ratio and Product Estimators for Finite Population Mean in Double Sampling

2016 ◽  
Vol 36 (3) ◽  
Author(s):  
Housila P. Singh ◽  
Gajendra K. Vishwakarma
Keyword(s):  
Empirical Study ◽  
Finite Population ◽  
Auxiliary Information ◽  
Double Sampling ◽  
Population Mean ◽  
Sampling Ratio

This paper presents exponential ratio and product estimators for estimating finite population mean using auxiliary information in double sampling and analyzes their properties. These estimators are compared for their precision with simple mean per unit, usual double sampling ratio and product estimators. An empirical study is also carried out to judge the merits of the suggested estimators.

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

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Manzoor Khan ◽  
Javid Shabbir ◽  
Zawar Hussain ◽  
Bander Al-Zahrani
Keyword(s):  
Empirical Study ◽  
Mean Square Error ◽  
Finite Population ◽  
Degree Of Approximation ◽  
Double Sampling ◽  
Mean Square ◽  
Population Mean ◽  
Class Of Estimators ◽  
Better Than

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.

Ratio-Cum-Product Type Estimator of Finite Population Mean in Case of Post Stratification

2016 ◽  
Vol 5 (1) ◽  
pp. 103-106
Author(s):  
Rajesh Tailor ◽  
Hilal A. Lone ◽  
Rajiv Pandey ◽  
Manoj Kumar
Keyword(s):  
Finite Population ◽  
Product Type ◽  
Population Mean ◽  
Post Stratification

Exponential ratio and product type estimators of finite population mean

2016 ◽  
Vol 19 (1) ◽  
pp. 55-71 ◽  
Author(s):  
Uzma Yasmeen ◽  
Muhammad Noor ul Amin ◽  
Muhammad Hanif
Keyword(s):  
Finite Population ◽  
Product Type ◽  
Population Mean

scholarly journals ESTIMATION OF POPULATION VARIANCE IN LOG – PRODUCT TYPE ESTIMATORS UNDER DOUBLE SAMPLING SCHEME

2019 ◽  
pp. 11-20
Author(s):  
Prabhakar Mishra ◽  
Rajesh Singh ◽  
Supriya Khare
Keyword(s):  
Random Sampling ◽  
Auxiliary Information ◽  
Simple Random Sampling ◽  
Product Type ◽  
Sampling Scheme ◽  
Double Sampling ◽  
Population Variance ◽  
Population Mean ◽  
Ancillary Information

It is experienced that auxiliary information when suitably incorporated yields more efficient and precise estimates. Mishra et al. (2017) have introduced a log type estimator for estimating unknown population mean using ancillary information in simple random sampling. Here we propose an improved log-product type estimator for population variance under double sampling. Properties of the estimators are studied both mathematically and numerically.  

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