2005
DOI: 10.18637/jss.v012.i06
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spatstat: AnRPackage for Analyzing Spatial Point Patterns

Abstract: Abstractspatstat is a package for analyzing spatial point pattern data. Its functionality includes exploratory data analysis, model-fitting, and simulation. It is designed to handle realistic datasets, including inhomogeneous point patterns, spatial sampling regions of arbitrary shape, extra covariate data, and 'marks' attached to the points of the point pattern.A unique feature of spatstat is its generic algorithm for fitting point process models to point pattern data. The interface to this algorithm is a fun… Show more

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Cited by 2,032 publications
(1,665 citation statements)
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References 68 publications
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“…The bandwidths and the extraction maps were produced using the packages sm (Bowman and Azzalini, 2007) and spatstat (Baddeley and Turner, 2005) in R 2.9 software (www.R-project.org) respectively. The extraction maps obtained were represented using ArcGIS 9.2.…”
Section: Spatial Explorationmentioning
confidence: 99%
“…The bandwidths and the extraction maps were produced using the packages sm (Bowman and Azzalini, 2007) and spatstat (Baddeley and Turner, 2005) in R 2.9 software (www.R-project.org) respectively. The extraction maps obtained were represented using ArcGIS 9.2.…”
Section: Spatial Explorationmentioning
confidence: 99%
“…Los hallazgos que no se han documentado tridimensionalmente en la excavación (los que proceden de las labores de criba y lavado de sedimentos) se generan dentro del volumen de la UE correspondiente con una rutina en la que intervienen las librerías foreign (R Core Team, 2016), spatstat (Baddeley & Turner, 2005) envolvente mínima 3D de los datos tomados en la cueva, se generan de forma aleatoria, tantos puntos como hallazgos, que luego se introducen de manera definitiva en la base de datos. Esta tarea es quizás la más novedosa metodológicamente hablando, porque en un paso previo se genera el volumen de cada una de las UUEE y posteriormente se generan los hallazgos que se han recuperado en cada una de ellas, siendo también posible introducir los volúmenes de las UUEE generados previamente.…”
Section: Metodologíaunclassified
“…Here, = 30 represents a good value to compromise between simulation accuracy and computation load [9]. Carlo sampling trials [7]. This mean upper bound can under-estimate, because it is not an absolute upper bound, i.e.…”
Section: (12)mentioning
confidence: 99%