Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Auxiliary attribute (2)
- Efficiency (2)
- Simple random sampling (2)
- Auxiliary variables (1)
- Auxiliary variate (1)
-
- Bias (1)
- Correlation Coefficient of Interval Neutrosophic Set (1)
- Family of estimators (1)
- Mean square error (1)
- Mean-squared error (1)
- Measurement error (1)
- Neutrosophic Set (1)
- Observational error (1)
- Phi correlation (1)
- Point bi-serial correlation (1)
- Point biserial correlation (1)
- Ratio estimator (1)
- Two-phase sampling (1)
- Weighted Correlation Coefficient of Interval Neutrosophic Set (1)
Articles 1 - 5 of 5
Full-Text Articles in Applied Statistics
A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache
A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
This paper deals with the problem of estimating the finite population mean when some information on auxiliary attribute is available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The results have been illustrated numerically by taking empirical population considered in the literature.
A Generalized Family Of Estimators For Estimating Population Mean Using Two Auxiliary Attributes, Sachin Malik, Rajesh Singh, Florentin Smarandache
A Generalized Family Of Estimators For Estimating Population Mean Using Two Auxiliary Attributes, Sachin Malik, Rajesh Singh, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
This paper deals with the problem of estimating the finite population mean when some information on two auxiliary attributes are available. A class of estimators is defined which includes the estimators recently proposed by Malik and Singh (2012), Naik and Gupta (1996) and Singh et al. (2007) as particular cases. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The study is also extended to two-phase sampling. The results have been illustrated numerically by taking empirical population considered in the literature.
Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache
Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.
A General Family Of Dual To Ratio-Cum-Product Estimator In Sample Surveys, Florentin Smarandache, Rajesh Singh, Mukesh Kumar, Pankaj Chauhan, Nirmala Sawan
A General Family Of Dual To Ratio-Cum-Product Estimator In Sample Surveys, Florentin Smarandache, Rajesh Singh, Mukesh Kumar, Pankaj Chauhan, Nirmala Sawan
Branch Mathematics and Statistics Faculty and Staff Publications
This paper presents a family of dual to ratio-cum-product estimators for the finite population mean. Under simple random sampling without replacement (SRSWOR) scheme, expressions of the bias and mean-squared error (MSE) up to the first order of approximation are derived. We show that the proposed family is more efficient than usual unbiased estimator, ratio estimator, product estimator, Singh estimator (1967), Srivenkataramana (1980) and Bandyopadhyaya estimator (1980) and Singh et al. (2005) estimator. An empirical study is carried out to illustrate the performance of the constructed estimator over others.
Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh
Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh
Branch Mathematics and Statistics Faculty and Staff Publications
This article addresses the problem of estimating the population mean using auxiliary information in the presence of measurement errors.