A computationally efficient method for delineating irregularly shaped spatial clusters

Autor:	Juan Carlos Duque, Alejandro Betancourt, Ermilson Velasquez, Jose Franco, Jared Aldstadt
Rok vydání:	2010
Předmět:	Economics and Econometrics Computational complexity theory Computer science Georeference Geography Planning and Development Amoeba (mathematics) Spatial clustering Data mining computer.software_genre Spatial analysis computer Algorithm Statistic
Zdroj:	Journal of Geographical Systems. 13:355-372
ISSN:	1435-5949 1435-5930
DOI:	10.1007/s10109-010-0137-1
Popis:	In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327–343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::df62539006f74f450232fcc8685c0d0c https://doi.org/10.1007/s10109-010-0137-1 Zobrazit plný text záznamu Full text from SpringerLink