D-STEM v2:功能时空数据建模软件

IF 5.4 2区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Statistical Software Pub Date : 2021-01-01 DOI:10.18637/jss.v099.i10

Yaqiong Wang,Francesco Finazzi,Alessandro Fassò

{"title":"D-STEM v2:功能时空数据建模软件","authors":"Yaqiong Wang,Francesco Finazzi,Alessandro Fassò","doi":"10.18637/jss.v099.i10","DOIUrl":null,"url":null,"abstract":"Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time. The MATLAB D-STEM v1 software package was first introduced for modelling multivariate space-time data and has been recently extended to D-STEM v2 to handle functional data indexed across space and over time. This paper introduces the new modelling capabilities of DSTEM v2 as well as the complexity reduction techniques required when dealing with large data sets. Model estimation, validation and dynamic kriging are demonstrated in two case studies, one related to ground-level air quality data in Beijing, China, and the other one related to atmospheric profile data collected globally through radio sounding.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":"83 11","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data\",\"authors\":\"Yaqiong Wang,Francesco Finazzi,Alessandro Fassò\",\"doi\":\"10.18637/jss.v099.i10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time. The MATLAB D-STEM v1 software package was first introduced for modelling multivariate space-time data and has been recently extended to D-STEM v2 to handle functional data indexed across space and over time. This paper introduces the new modelling capabilities of DSTEM v2 as well as the complexity reduction techniques required when dealing with large data sets. Model estimation, validation and dynamic kriging are demonstrated in two case studies, one related to ground-level air quality data in Beijing, China, and the other one related to atmospheric profile data collected globally through radio sounding.\",\"PeriodicalId\":17237,\"journal\":{\"name\":\"Journal of Statistical Software\",\"volume\":\"83 11\",\"pages\":\"\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.18637/jss.v099.i10\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.18637/jss.v099.i10","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 1

摘要

功能时空数据自然出现在许多环境和气候应用中，其中数据是在三维空间中随时间收集的。MATLAB D-STEM v1软件包最初用于建模多元时空数据，最近已扩展到D-STEM v2，以处理跨空间和时间索引的功能数据。本文介绍了DSTEM v2的新建模功能，以及在处理大型数据集时所需的复杂性降低技术。模型估计、验证和动态克里格在两个案例中进行了演示，一个与中国北京的地面空气质量数据有关，另一个与通过无线电探测收集的全球大气剖面数据有关。

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

D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data

Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time. The MATLAB D-STEM v1 software package was first introduced for modelling multivariate space-time data and has been recently extended to D-STEM v2 to handle functional data indexed across space and over time. This paper introduces the new modelling capabilities of DSTEM v2 as well as the complexity reduction techniques required when dealing with large data sets. Model estimation, validation and dynamic kriging are demonstrated in two case studies, one related to ground-level air quality data in Beijing, China, and the other one related to atmospheric profile data collected globally through radio sounding.

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

Journal of Statistical Software 工程技术-计算机：跨学科应用

CiteScore

10.70

自引率

1.70%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.