R Package Development for Difference Benchmarking in Small Area Estimation Fay-Herriot Model

Zaza Yuda Perwira, A. Ubaidillah
{"title":"R Package Development for Difference Benchmarking in Small Area Estimation Fay-Herriot Model","authors":"Zaza Yuda Perwira, A. Ubaidillah","doi":"10.34123/icdsos.v2021i1.69","DOIUrl":null,"url":null,"abstract":"In recent decades, the use of small area estimation (SAE) for producing official statistics has been widely recognized by many National Statistics Offices including BPS-Statistics Indonesia. For official statistics usage, the aggregation of small area estimates is expected to be numerically consistent and more efficient than the aggregation of the unbiased direct estimates that cannot be guaranteed by Fay-Herriot model. Simulation experiments are performed to assess the behaviour of the difference benchmarking method Fay-Herriot model and to compare the mean squared error (MSE). The result shows that the difference benchmarking method can produce a consistent aggregation towards the direct estimation. Furthermore, an R package was built to implement the method that is easier to be used and is already available in the CRAN website. The package has been evaluated using validity (simulation), performance, case studies, and usability tests. These evaluations show that the package is suitable for use. Implementation of the methodology is also be applied to estimate average household consumption per capita expenditure in districts in D.I. Yogyakarta province, Indonesia 2019","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The International Conference on Data Science and Official Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34123/icdsos.v2021i1.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In recent decades, the use of small area estimation (SAE) for producing official statistics has been widely recognized by many National Statistics Offices including BPS-Statistics Indonesia. For official statistics usage, the aggregation of small area estimates is expected to be numerically consistent and more efficient than the aggregation of the unbiased direct estimates that cannot be guaranteed by Fay-Herriot model. Simulation experiments are performed to assess the behaviour of the difference benchmarking method Fay-Herriot model and to compare the mean squared error (MSE). The result shows that the difference benchmarking method can produce a consistent aggregation towards the direct estimation. Furthermore, an R package was built to implement the method that is easier to be used and is already available in the CRAN website. The package has been evaluated using validity (simulation), performance, case studies, and usability tests. These evaluations show that the package is suitable for use. Implementation of the methodology is also be applied to estimate average household consumption per capita expenditure in districts in D.I. Yogyakarta province, Indonesia 2019
小面积估计Fay-Herriot模型差分基准的R包开发
近几十年来,使用小面积估计(SAE)来制作官方统计数据已被包括BPS-Statistics Indonesia在内的许多国家统计局广泛认可。对于官方统计使用,小区域估计的汇总预计在数值上是一致的,并且比Fay-Herriot模型不能保证的无偏直接估计的汇总更有效。仿真实验评估了差异基准法Fay-Herriot模型的行为,并比较了均方误差(MSE)。结果表明,差分基准法可以对直接估计产生一致的聚合。此外,还构建了一个R包来实现更容易使用的方法,并且已经可以在CRAN网站上获得。软件包已经通过有效性(模拟)、性能、案例研究和可用性测试进行了评估。这些评价表明,该软件包是适合使用的。该方法也被用于估计2019年印度尼西亚日惹省各区的平均家庭消费人均支出
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信