扫描统计调整为全球空间自相关

IF 3.3 3区地球科学 Q1 GEOGRAPHY

Geographical Analysis Pub Date : 2021-07-02 DOI:10.1111/gean.12301

Peter A. Rogerson

{"title":"扫描统计调整为全球空间自相关","authors":"Peter A. Rogerson","doi":"10.1111/gean.12301","DOIUrl":null,"url":null,"abstract":"Failure to account for global spatial autocorrelation when using scan statistics to find clusters generated by local processes will result in P-values that are too low, and consequently, spurious findings of statistical significance are not uncommon. The presence of global spatial autocorrelation also decreases the ability to reject false null hypotheses and it is therefore more difficult to find local clusters when they exist. By estimating the degree of global autocorrelation and using that estimate to transform the data, it is then possible to apply scan statistics to the transformed data. This results in a reduction in the likelihood of spurious finding of statistical significance when local clusters do not exist.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"54 4","pages":"739-751"},"PeriodicalIF":3.3000,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/gean.12301","citationCount":"4","resultStr":"{\"title\":\"Scan Statistics Adjusted for Global Spatial Autocorrelation\",\"authors\":\"Peter A. Rogerson\",\"doi\":\"10.1111/gean.12301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Failure to account for global spatial autocorrelation when using scan statistics to find clusters generated by local processes will result in P-values that are too low, and consequently, spurious findings of statistical significance are not uncommon. The presence of global spatial autocorrelation also decreases the ability to reject false null hypotheses and it is therefore more difficult to find local clusters when they exist. By estimating the degree of global autocorrelation and using that estimate to transform the data, it is then possible to apply scan statistics to the transformed data. This results in a reduction in the likelihood of spurious finding of statistical significance when local clusters do not exist.\",\"PeriodicalId\":12533,\"journal\":{\"name\":\"Geographical Analysis\",\"volume\":\"54 4\",\"pages\":\"739-751\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2021-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1111/gean.12301\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geographical Analysis\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/gean.12301\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geographical Analysis","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/gean.12301","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}

引用次数: 4

摘要

当使用扫描统计来查找由局部过程生成的聚类时，如果不能考虑全局空间自相关性，将导致p值过低，因此，统计显著性的虚假发现并不罕见。全局空间自相关的存在也降低了拒绝错误零假设的能力，因此当存在局部聚类时更难以找到它们。通过估计全局自相关的程度并使用该估计来转换数据，然后可以将扫描统计信息应用于转换后的数据。当局部聚类不存在时，这可以减少统计显著性的虚假发现的可能性。

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

Scan Statistics Adjusted for Global Spatial Autocorrelation

Failure to account for global spatial autocorrelation when using scan statistics to find clusters generated by local processes will result in P-values that are too low, and consequently, spurious findings of statistical significance are not uncommon. The presence of global spatial autocorrelation also decreases the ability to reject false null hypotheses and it is therefore more difficult to find local clusters when they exist. By estimating the degree of global autocorrelation and using that estimate to transform the data, it is then possible to apply scan statistics to the transformed data. This results in a reduction in the likelihood of spurious finding of statistical significance when local clusters do not exist.

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

Geographical Analysis GEOGRAPHY-

CiteScore

8.70

自引率

5.60%

发文量

期刊介绍： First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.