Non-Parametric Analysis of Spatial and Spatio-Temporal Point Patterns

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS R Journal Pub Date : 2023-08-26 DOI:10.32614/rj-2023-025
Jonatan A. González, Paula Moraga
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Abstract

The analysis of spatial and spatio-temporal point patterns is becoming increasingly necessary, given the rapid emergence of geographically and temporally indexed data in a wide range of fields. Non-parametric point pattern methods are a highly adaptable approach to answering questions about the real-world using complex data in the form of collections of points. Several methodological advances have been introduced in the last few years. This paper examines the current methodology, including the most recent developments in estimation and computation, and shows how various R packages can be combined to run a set of non-parametric point pattern analyses in a guided and intuitive way. An example of non-specific gastrointestinal disease reports in Hampshire, UK, from 2001 to 2003 is used to illustrate the methods, procedures and interpretations.
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时空点模式的非参数分析
鉴于地理和时间索引数据在广泛领域的迅速出现,空间和时空点模式的分析变得越来越必要。非参数点模式方法是一种高度适应性的方法,可以使用点集合形式的复杂数据来回答有关现实世界的问题。在过去几年中,已经介绍了几种方法上的进步。本文研究了当前的方法,包括估计和计算方面的最新发展,并展示了如何将各种R包组合在一起,以指导和直观的方式运行一组非参数点模式分析。在汉普郡,英国,从2001年至2003年的非特异性胃肠道疾病报告的一个例子是用来说明方法,程序和解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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