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New estimators for estimating population total: an application to water demand in Thailand under unequal probability sampling without replacement for missing data
Water shortage could play an imperative role in the future due to an influx of water demand when compared to water supplies. Inadequate water could damage human life and other aspects related to living. This serious issue can be prevented by estimating the demand for water to bridge the small gap be...
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| Published in: | PeerJ (San Francisco, CA) CA), 2022-12, Vol.10, p.e14551-e14551, Article e14551 |
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| cited_by | cdi_FETCH-LOGICAL-c573t-5fd45553b4b42e63c5d7232e2b5569e11b5aca1e4f569069d9f7190be14d6daa3 |
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| cites | cdi_FETCH-LOGICAL-c573t-5fd45553b4b42e63c5d7232e2b5569e11b5aca1e4f569069d9f7190be14d6daa3 |
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| container_title | PeerJ (San Francisco, CA) |
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| creator | Ponkaew, Chugiat Lawson, Nuanpan |
| description | Water shortage could play an imperative role in the future due to an influx of water demand when compared to water supplies. Inadequate water could damage human life and other aspects related to living. This serious issue can be prevented by estimating the demand for water to bridge the small gap between demand and supplies for water. Some water consumption data recorded daily may be missing and could affect the estimated value of water demand. In this article, new ratio estimators for estimating population total are proposed under unequal probability sampling without replacement when data are missing. Two situations are considered: known or unknown mean of an auxiliary variable and missing data are missing at random for both study and auxiliary variables. The variance and associated estimators of the proposed estimators are investigated under a reverse framework. The proposed estimators are applied to data from simulation studies and empirical data on water demand in Thailand which contain some missing values, to assess the efficacies of the estimators. |
| doi_str_mv | 10.7717/peerj.14551 |
| format | article |
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Inadequate water could damage human life and other aspects related to living. This serious issue can be prevented by estimating the demand for water to bridge the small gap between demand and supplies for water. Some water consumption data recorded daily may be missing and could affect the estimated value of water demand. In this article, new ratio estimators for estimating population total are proposed under unequal probability sampling without replacement when data are missing. Two situations are considered: known or unknown mean of an auxiliary variable and missing data are missing at random for both study and auxiliary variables. The variance and associated estimators of the proposed estimators are investigated under a reverse framework. 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This is an open access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. 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Inadequate water could damage human life and other aspects related to living. This serious issue can be prevented by estimating the demand for water to bridge the small gap between demand and supplies for water. Some water consumption data recorded daily may be missing and could affect the estimated value of water demand. In this article, new ratio estimators for estimating population total are proposed under unequal probability sampling without replacement when data are missing. Two situations are considered: known or unknown mean of an auxiliary variable and missing data are missing at random for both study and auxiliary variables. The variance and associated estimators of the proposed estimators are investigated under a reverse framework. 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| subjects | Computer Simulation Data Interpretation, Statistical Developing countries Ecohydrology Food, Water and Energy Nexus Humans Kurtosis LDCs Logistic regression Mean square errors Missing data Natural Resource Management Nonlinear estimator Population total Probability Rain Replantation Sampling Taylor linearization approach Thailand Unequal probability sampling without replacement Variables Water Water demand Water shortages Water supply |
| title | New estimators for estimating population total: an application to water demand in Thailand under unequal probability sampling without replacement for missing data |
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