Some linear regression type ratio exponential estimators for estimating the population mean based on quartile deviation and deciles
Shakti Prasad
This paper deals some linear regression type ratio exponential estimators for estimating the population mean using the known values of quartile deviation and deciles of an auxiliary variable in survey sampling. The expressions of the bias and the mean square error of the suggested estimators have been derived. It was compared with the usual mean, usual ratio (Cochran (1977), Kadilar and Cingi (2004, 2006) and Subzar et al. (2017) estimators. After comparison, the condition which makes the suggested estimators more efficient than others is found. To verify the theoretical results, numerical results are performed on two natural population data sets.
Year of publication: |
2020
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Authors: | Prasad, Shakti |
Published in: |
Statistics in transition : an international journal of the Polish Statistical Association and Statistics Poland. - Warszawa : GUS, ISSN 2450-0291, ZDB-ID 2235641-1. - Vol. 21.2020, 5, p. 85-98
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Subject: | Bias | Mean square error (MSE) | Auxiliary variable | Relative Efficiency (%) | Schätztheorie | Estimation theory |
Saved in:
freely available
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.21307/stattrans-2020-056 [DOI] hdl:10419/236806 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012655747
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