A Review of Chain-Type Estimators and a New Chain-Type Multivariate Regression Approach for Population Mean Under Two-Occasion Successive Sampling

This paper presents the problem of estimating the population mean on current occasion in two-occasions successive sampling using multiauxiliary variate at both the occasions. We have presented the comprehensive review of the work based on chain-type estimators using single and multiauxiliary variate...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences, India, Section A, physical sciences India, Section A, physical sciences, 2017-03, Vol.87 (1), p.31-56
Main Authors: Singh, Housila P., Pal, Surya K.
Format: Article
Language:English
Subjects:
Applied and Technical Physics
Atomic
Chains
Estimation
Estimators
Molecular
Optical and Plasma Physics
Optimization
Physics
Physics and Astronomy
Quantum Physics
Regression
Research Article
Sampling
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Summary:This paper presents the problem of estimating the population mean on current occasion in two-occasions successive sampling using multiauxiliary variate at both the occasions. We have presented the comprehensive review of the work based on chain-type estimators using single and multiauxiliary variate(s) at both the occasions. A new chain-type multivariate regression estimator for estimating the population mean on current occasion in two-occasion successive sampling is also suggested. Optimum replacement policy relevant to the proposed estimation procedure has been discussed. It has been shown empirically that the proposed multivariate regression estimator is more efficient than the simple mean estimator when there is no matching, the optimal successive sampling estimator when no additional auxiliary information is used and other estimator based on multiauxiliary variates.
ISSN:0369-8203
2250-1762
DOI:10.1007/s40010-016-0313-x