An improved efficient class of estimators for the population variance

2021 ◽  
Author(s):  
Iqra Niaz ◽  
Aamir Sanaullah ◽  
Iram Saleem ◽  
Javid Shabbir
Keyword(s):  
Population Variance ◽  
Class Of Estimators

An improved class of estimators for the population variance

2013 ◽  
Vol 8 (3) ◽  
pp. 229-238 ◽  
Author(s):  
Ramkrishna S. Solanki ◽  
Housila P. Singh
Keyword(s):  
Population Variance ◽  
Class Of Estimators

A New Improved Class of Estimators For The Population Variance

2016 ◽  
Vol 5 (3) ◽  
pp. 385-392
Author(s):  
Subhash Kumar Yadav ◽  
Sant Sharan Mishra ◽  
Shakti Kumar ◽  
Cem Kadilar
Keyword(s):  
Population Variance ◽  
Class Of Estimators

scholarly journals Generalized Class of Estimators for Population Variance Using Auxiliary Attribute

2015 ◽  
Vol 2 (4) ◽  
pp. 499-508 ◽  
Author(s):  
Nitesh K. Adichwal ◽  
Prayas Sharma ◽  
Hemant K. Verma ◽  
Rajesh Singh
Keyword(s):  
Population Variance ◽  
Class Of Estimators

scholarly journals Ameliorated Class of Estimators of Finite Population Variance

2020 ◽  
pp. 1-14
Author(s):  
J. O. Muili ◽  
E. N. Agwamba ◽  
A. B. Odeyale ◽  
A. Adebiyi
Keyword(s):  
Finite Population ◽  
Population Variance ◽  
First Order ◽  
Class Of Estimators ◽  
The Mean ◽  
Ratio Estimators ◽  
Mean Square Errors ◽  
Theoretical Results ◽  
Percentage Relative Efficiency ◽  
Taylor’S Series

A class of ratio estimators of finite population variance is proposed in this study. The properties of the proposed estimators have been derived using Taylor’s Series method up to first order of approximation. The efficiency conditions which are the mean square errors (MSEs) and percentage relative efficiency (PRE) of the proposed estimators over existing estimators have been established. The analytical illustration was also conducted to affirm the theoretical results. The results of the empirical study revealed that the proposed estimators are more efficient than the existing estimators considered in the study.

scholarly journals On Construction of Modified Class of Estimators for Population Variance using Auxiliary Attribute

2020 ◽  
Vol 4 (9) ◽  
pp. 109-119
Keyword(s):  
Relative Efficiency ◽  
Numerical Study ◽  
Order Of Approximation ◽  
Population Variance ◽  
First Order ◽  
Class Of Estimators

In this paper, an improved estimator for population variance has been proposed to improvise the log-type estimators proposed by Kumari et al. (2019). The properties of proposed estimators are derived up to the first order of approximation. The proposed estimatorfound to be betterthan the existing estimatorsin the sense of mean squraed error and percent relative efficiency. A numerical study is included to support the use of the suggested classes of estimators.

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