This paper describes theoretical estimation of domains mean using double sampling with a non-linear cost function in the presence of non-response. The estimation of domain mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response in the second phase sampling. The expression of the biases and mean square errors of the proposed estimators are obtained. The optimal stratum sample sizes for given set of non-linear cost function are developed.
| Published in | Science Journal of Applied Mathematics and Statistics (Volume 6, Issue 1) |
| DOI | 10.11648/j.sjams.20180601.14 |
| Page(s) | 28-42 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Double Sampling for Ratio Estimation, Domain Mean, Auxiliary Variable, Non-Linear Cost Function and Non-Response
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APA Style
Alila David Anekeya, Ouma Christopher Onyango, Nyongesa Kennedy. (2018). Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response. Science Journal of Applied Mathematics and Statistics, 6(1), 28-42. https://doi.org/10.11648/j.sjams.20180601.14
ACS Style
Alila David Anekeya; Ouma Christopher Onyango; Nyongesa Kennedy. Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response. Sci. J. Appl. Math. Stat. 2018, 6(1), 28-42. doi: 10.11648/j.sjams.20180601.14
AMA Style
Alila David Anekeya, Ouma Christopher Onyango, Nyongesa Kennedy. Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response. Sci J Appl Math Stat. 2018;6(1):28-42. doi: 10.11648/j.sjams.20180601.14
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Download@article{10.11648/j.sjams.20180601.14,
author = {Alila David Anekeya and Ouma Christopher Onyango and Nyongesa Kennedy},
title = {Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response},
journal = {Science Journal of Applied Mathematics and Statistics},
volume = {6},
number = {1},
pages = {28-42},
doi = {10.11648/j.sjams.20180601.14},
url = {https://doi.org/10.11648/j.sjams.20180601.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20180601.14},
abstract = {This paper describes theoretical estimation of domains mean using double sampling with a non-linear cost function in the presence of non-response. The estimation of domain mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response in the second phase sampling. The expression of the biases and mean square errors of the proposed estimators are obtained. The optimal stratum sample sizes for given set of non-linear cost function are developed.},
year = {2018}
}
TY - JOUR T1 - Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response AU - Alila David Anekeya AU - Ouma Christopher Onyango AU - Nyongesa Kennedy Y1 - 2018/02/15 PY - 2018 N1 - https://doi.org/10.11648/j.sjams.20180601.14 DO - 10.11648/j.sjams.20180601.14 T2 - Science Journal of Applied Mathematics and Statistics JF - Science Journal of Applied Mathematics and Statistics JO - Science Journal of Applied Mathematics and Statistics SP - 28 EP - 42 PB - Science Publishing Group SN - 2376-9513 UR - https://doi.org/10.11648/j.sjams.20180601.14 AB - This paper describes theoretical estimation of domains mean using double sampling with a non-linear cost function in the presence of non-response. The estimation of domain mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response in the second phase sampling. The expression of the biases and mean square errors of the proposed estimators are obtained. The optimal stratum sample sizes for given set of non-linear cost function are developed. VL - 6 IS - 1 ER -
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