基于泊松的回归模型的预测区间

IF 4.4 2区数学 Q1 STATISTICS & PROBABILITY

Wiley Interdisciplinary Reviews-Computational Statistics Pub Date : 2021-06-21 DOI:10.1002/wics.1568

Taeho Kim, Benjamin Lieberman, G. Luta, Edsel A. Peña

{"title":"基于泊松的回归模型的预测区间","authors":"Taeho Kim, Benjamin Lieberman, G. Luta, Edsel A. Peña","doi":"10.1002/wics.1568","DOIUrl":null,"url":null,"abstract":"This paper provides a review of the literature regarding methods for constructing prediction intervals for counting variables, with particular focus on those whose distributions are Poisson or derived from Poisson and with an over‐dispersion property. Independent and identically distributed models and regression models are both considered. The motivating problem for this review is that of predicting the number of daily and cumulative cases or deaths attributable to COVID‐19 at a future date.","PeriodicalId":47779,"journal":{"name":"Wiley Interdisciplinary Reviews-Computational Statistics","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/wics.1568","citationCount":"2","resultStr":"{\"title\":\"Prediction intervals for Poisson‐based regression models\",\"authors\":\"Taeho Kim, Benjamin Lieberman, G. Luta, Edsel A. Peña\",\"doi\":\"10.1002/wics.1568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides a review of the literature regarding methods for constructing prediction intervals for counting variables, with particular focus on those whose distributions are Poisson or derived from Poisson and with an over‐dispersion property. Independent and identically distributed models and regression models are both considered. The motivating problem for this review is that of predicting the number of daily and cumulative cases or deaths attributable to COVID‐19 at a future date.\",\"PeriodicalId\":47779,\"journal\":{\"name\":\"Wiley Interdisciplinary Reviews-Computational Statistics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2021-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/wics.1568\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wiley Interdisciplinary Reviews-Computational Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/wics.1568\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Computational Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/wics.1568","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}

引用次数: 2

摘要

本文回顾了关于构造计数变量预测区间方法的文献，特别关注那些分布为泊松或由泊松导出并具有过分散性质的预测区间。同时考虑了独立同分布模型和回归模型。本综述的激励问题是预测未来日期可归因于COVID - 19的每日和累计病例或死亡人数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Prediction intervals for Poisson‐based regression models

This paper provides a review of the literature regarding methods for constructing prediction intervals for counting variables, with particular focus on those whose distributions are Poisson or derived from Poisson and with an over‐dispersion property. Independent and identically distributed models and regression models are both considered. The motivating problem for this review is that of predicting the number of daily and cumulative cases or deaths attributable to COVID‐19 at a future date.

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

Wiley Interdisciplinary Reviews-Computational Statistics STATISTICS & PROBABILITY-

CiteScore

6.20

自引率

0.00%

发文量