{"title":"A generic test for the similarity of spatial data","authors":"R. Kirsten, I. Fabris-Rotelli","doi":"10.37920/SASJ.2021.55.1.5","DOIUrl":null,"url":null,"abstract":"Two spatial data sets are considered to be similar if they originate from the same stochastic process in terms of their spatial structure. Many tests have been developed over recent years to test the similarity of certain types of spatial data, such as spatial point patterns, geostatistical data and images. This research proposes a generic spatial similarity test able to handle various types of spatial data, for example images (modelled spatially), point patterns, marked point patterns, geostatistical data and lattice patterns. A simulation study is done in order to test the method for each spatial data set. After the simulation study, it was concluded that the proposed spatial similarity test is not sensitive to the user-defined resolution of the pixel image representation. From the simulation study, the proposed spatial similarity test performs well on lattice data, some of the unmarked point patterns and the marked point patterns with discrete marks. We illustrate this test on property prices in the City of Cape Town and the City of Johannesburg, South Africa.","PeriodicalId":53997,"journal":{"name":"SOUTH AFRICAN STATISTICAL JOURNAL","volume":"55 1","pages":"55-71"},"PeriodicalIF":0.4000,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SOUTH AFRICAN STATISTICAL JOURNAL","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37920/SASJ.2021.55.1.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Two spatial data sets are considered to be similar if they originate from the same stochastic process in terms of their spatial structure. Many tests have been developed over recent years to test the similarity of certain types of spatial data, such as spatial point patterns, geostatistical data and images. This research proposes a generic spatial similarity test able to handle various types of spatial data, for example images (modelled spatially), point patterns, marked point patterns, geostatistical data and lattice patterns. A simulation study is done in order to test the method for each spatial data set. After the simulation study, it was concluded that the proposed spatial similarity test is not sensitive to the user-defined resolution of the pixel image representation. From the simulation study, the proposed spatial similarity test performs well on lattice data, some of the unmarked point patterns and the marked point patterns with discrete marks. We illustrate this test on property prices in the City of Cape Town and the City of Johannesburg, South Africa.
期刊介绍:
The journal will publish innovative contributions to the theory and application of statistics. Authoritative review articles on topics of general interest which are not readily accessible in a coherent form, will be also be considered for publication. Articles on applications or of a general nature will be published in separate sections and an author should indicate which of these sections an article is intended for. An applications article should normally consist of the analysis of actual data and need not necessarily contain new theory. The data should be made available with the article but need not necessarily be part of it.