Improved ratio type generalized class of estimators in two phase adaptive cluster sampling
In this paper, an improved ratio type class of estimators in the two phase Adaptive Cluster Sampling (ACS) design under the transformed population approach has been proposed. The generalized expressions of Bias and Mean Squared Error (MSE) have been obtained up to the first order of approximation. N...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
REA Press
2024-03-01
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| Series: | Big Data and Computing Visions |
| Subjects: | |
| Online Access: | https://www.bidacv.com/article_194519_8a0223e86cc1c735ec7f2f0e77b8414f.pdf |
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| Summary: | In this paper, an improved ratio type class of estimators in the two phase Adaptive Cluster Sampling (ACS) design under the transformed population approach has been proposed. The generalized expressions of Bias and Mean Squared Error (MSE) have been obtained up to the first order of approximation. New member estimators are developed from the proposed class and their performance against competing existing estimators are evaluated using various empirical studies. The novelty of this design and the new estimators developed therein are further demonstrated using a real data study where the new developed estimators are used to estimate the average number of thorny plants in plateaus of Western Ghats of Sahyadri from Goa to Varandha Ghat (Bhor, Maharashtra, India). |
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| ISSN: | 2783-4956 2821-014X |