双变量正态分布的曲面曲率分析:土耳其新冠肺炎数据的应用

IF 2.3 0 GEOGRAPHY
Vahide Bulut, S. Korukoglu
{"title":"双变量正态分布的曲面曲率分析:土耳其新冠肺炎数据的应用","authors":"Vahide Bulut, S. Korukoglu","doi":"10.15196/RS120401","DOIUrl":null,"url":null,"abstract":"Principal curvatures have free-form rigid surfaces' invariant features. Therefore they are widely used in several fields for various applications, such as determining the corresponding points between an object and a free-form scene. In this study, the authors analysed the surface curvature of a bivariate normal distribution. A novel approach for classifying bivariate normal surfaces based on curvature statistics concerning correlation structures is presented. The principal curvatures, Gaussian, and mean curvatures were obtained using the data generated from the bivariate normal distribution. The degree of dependency bivariate data directly affects the shape and curvature structures of the bivariate normal distribution surface. Different parameters, from uncorrelated to highly correlated variables, for the correlation of the bivariate normal distribution based on the data have been examined. The effects of the correlation on the distribution surface characteristics have been analysed individually and collectively. This study presents theoretical results in addition to the results of the simulation and real datasets. The simulation data presents the relationship between the independence of the variables and the uniformity of the kappa(n2) values. The other application is based on the curvature properties of the bivariate normal surface on Covid-19 as real data.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Surface curvature analysis of bivariate normal distribution: A Covid-19 data application on Turkey\",\"authors\":\"Vahide Bulut, S. Korukoglu\",\"doi\":\"10.15196/RS120401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Principal curvatures have free-form rigid surfaces' invariant features. Therefore they are widely used in several fields for various applications, such as determining the corresponding points between an object and a free-form scene. In this study, the authors analysed the surface curvature of a bivariate normal distribution. A novel approach for classifying bivariate normal surfaces based on curvature statistics concerning correlation structures is presented. The principal curvatures, Gaussian, and mean curvatures were obtained using the data generated from the bivariate normal distribution. The degree of dependency bivariate data directly affects the shape and curvature structures of the bivariate normal distribution surface. Different parameters, from uncorrelated to highly correlated variables, for the correlation of the bivariate normal distribution based on the data have been examined. The effects of the correlation on the distribution surface characteristics have been analysed individually and collectively. This study presents theoretical results in addition to the results of the simulation and real datasets. The simulation data presents the relationship between the independence of the variables and the uniformity of the kappa(n2) values. The other application is based on the curvature properties of the bivariate normal surface on Covid-19 as real data.\",\"PeriodicalId\":44388,\"journal\":{\"name\":\"Regional Statistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Regional Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15196/RS120401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15196/RS120401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 1

摘要

主曲率具有自由形式刚性曲面的不变特征。因此,它们被广泛应用于多个领域的各种应用,例如确定物体与自由形式场景之间的对应点。在这项研究中,作者分析了二元正态分布的表面曲率。提出了一种基于相关结构曲率统计的二元法向曲面分类方法。利用二元正态分布生成的数据得到主曲率、高斯曲率和平均曲率。二元数据的依赖程度直接影响二元正态分布曲面的形状和曲率结构。不同的参数,从不相关到高度相关的变量,对二元正态分布的相关性进行了基于数据的检验。对相关系数对分布面特性的影响分别进行了分析和综合分析。本研究除了给出仿真结果和实际数据集外,还给出了理论结果。仿真数据显示了变量的独立性与kappa(n2)值的均匀性之间的关系。另一个应用是基于Covid-19的二元法向曲面的曲率特性作为实际数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surface curvature analysis of bivariate normal distribution: A Covid-19 data application on Turkey
Principal curvatures have free-form rigid surfaces' invariant features. Therefore they are widely used in several fields for various applications, such as determining the corresponding points between an object and a free-form scene. In this study, the authors analysed the surface curvature of a bivariate normal distribution. A novel approach for classifying bivariate normal surfaces based on curvature statistics concerning correlation structures is presented. The principal curvatures, Gaussian, and mean curvatures were obtained using the data generated from the bivariate normal distribution. The degree of dependency bivariate data directly affects the shape and curvature structures of the bivariate normal distribution surface. Different parameters, from uncorrelated to highly correlated variables, for the correlation of the bivariate normal distribution based on the data have been examined. The effects of the correlation on the distribution surface characteristics have been analysed individually and collectively. This study presents theoretical results in addition to the results of the simulation and real datasets. The simulation data presents the relationship between the independence of the variables and the uniformity of the kappa(n2) values. The other application is based on the curvature properties of the bivariate normal surface on Covid-19 as real data.
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
Regional Statistics
Regional Statistics GEOGRAPHY-
CiteScore
5.30
自引率
52.20%
发文量
28
期刊介绍: The periodical welcomes studies, research and conference reports, book reviews, discussion articles reflecting on our former articles. The periodical welcomes articles from the following areas: regional statistics, regional science, social geography, regional planning, sociology, geographical information science Goals of the journal: high-level studies in the field of regional analyses, to encourage the exchange of views and discussion among researchers in the area of regional researches.
×
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