膨胀的Kumaraswamy回归及其在巴西供水和卫生方面的应用

IF 1.4 3区 数学 Q2 STATISTICS & PROBABILITY
F. M. Bayer, Francisco Cribari‐Neto, Jéssica Santos
{"title":"膨胀的Kumaraswamy回归及其在巴西供水和卫生方面的应用","authors":"F. M. Bayer, Francisco Cribari‐Neto, Jéssica Santos","doi":"10.1111/stan.12242","DOIUrl":null,"url":null,"abstract":"Models based on the Kumaraswamy law are used with variables that assume values in (0, 1). In some cases, however, the data contain zeros and/or ones, that is, there is data inflation. We introduce a class of regression models that can be used with such inflated data, namely: the class of inflated Kumaraswamy regression models. We consider inflation at zero, at one, and at both zero and one. We introduce the model and provide closed‐form expressions for its score vector and Fisher's information matrix. The proposed model is used to evaluate the impacts of different conditioning variables on the proportion of people who live in households with inadequate water supply and sewage in Brazilian municipalities. Our results reveal that policies directed to increasing the population share with college education in places where it is low are particularly effective in reducing the prevalence of people who live under inadequate sanitation conditions.","PeriodicalId":51178,"journal":{"name":"Statistica Neerlandica","volume":"30 1","pages":"453 - 481"},"PeriodicalIF":1.4000,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Inflated Kumaraswamy regressions with application to water supply and sanitation in Brazil\",\"authors\":\"F. M. Bayer, Francisco Cribari‐Neto, Jéssica Santos\",\"doi\":\"10.1111/stan.12242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Models based on the Kumaraswamy law are used with variables that assume values in (0, 1). In some cases, however, the data contain zeros and/or ones, that is, there is data inflation. We introduce a class of regression models that can be used with such inflated data, namely: the class of inflated Kumaraswamy regression models. We consider inflation at zero, at one, and at both zero and one. We introduce the model and provide closed‐form expressions for its score vector and Fisher's information matrix. The proposed model is used to evaluate the impacts of different conditioning variables on the proportion of people who live in households with inadequate water supply and sewage in Brazilian municipalities. Our results reveal that policies directed to increasing the population share with college education in places where it is low are particularly effective in reducing the prevalence of people who live under inadequate sanitation conditions.\",\"PeriodicalId\":51178,\"journal\":{\"name\":\"Statistica Neerlandica\",\"volume\":\"30 1\",\"pages\":\"453 - 481\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2021-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistica Neerlandica\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1111/stan.12242\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistica Neerlandica","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1111/stan.12242","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 4

摘要

基于Kumaraswamy定律的模型与假设值为(0,1)的变量一起使用。然而,在某些情况下,数据包含0和/或1,即存在数据膨胀。我们引入了一类可以用于这类膨胀数据的回归模型,即:膨胀Kumaraswamy回归模型。我们认为通货膨胀率为0,为1,同时为0和1。我们介绍了该模型,并给出了其分数向量和Fisher信息矩阵的封闭形式表达式。所提出的模型用于评估不同条件变量对巴西市政供水和污水不足家庭人口比例的影响。我们的研究结果表明,在教育水平较低的地方,旨在提高大学教育人口比例的政策在减少生活在卫生条件不佳的人群中尤为有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inflated Kumaraswamy regressions with application to water supply and sanitation in Brazil
Models based on the Kumaraswamy law are used with variables that assume values in (0, 1). In some cases, however, the data contain zeros and/or ones, that is, there is data inflation. We introduce a class of regression models that can be used with such inflated data, namely: the class of inflated Kumaraswamy regression models. We consider inflation at zero, at one, and at both zero and one. We introduce the model and provide closed‐form expressions for its score vector and Fisher's information matrix. The proposed model is used to evaluate the impacts of different conditioning variables on the proportion of people who live in households with inadequate water supply and sewage in Brazilian municipalities. Our results reveal that policies directed to increasing the population share with college education in places where it is low are particularly effective in reducing the prevalence of people who live under inadequate sanitation conditions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Statistica Neerlandica
Statistica Neerlandica 数学-统计学与概率论
CiteScore
2.60
自引率
6.70%
发文量
26
审稿时长
>12 weeks
期刊介绍: Statistica Neerlandica has been the journal of the Netherlands Society for Statistics and Operations Research since 1946. It covers all areas of statistics, from theoretical to applied, with a special emphasis on mathematical statistics, statistics for the behavioural sciences and biostatistics. This wide scope is reflected by the expertise of the journal’s editors representing these areas. The diverse editorial board is committed to a fast and fair reviewing process, and will judge submissions on quality, correctness, relevance and originality. Statistica Neerlandica encourages transparency and reproducibility, and offers online resources to make data, code, simulation results and other additional materials publicly available.
×
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:481959085
Book学术官方微信