spatstat.Knet-package: Extension to 'spatstat' for Large Datasets on a Linear...

In spatstat.Knet: Extension to 'spatstat' for Large Datasets on a Linear Network

Extension to 'spatstat' for Large Datasets on a Linear Network

Description

Extension to the 'spatstat' family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019).

Details

This is an extension to the spatstat package for the analysis of large data sets on linear networks.

Its main functionality is a memory-efficient algorithm for computing the estimate of the K function on a linear network, described in Rakshit et al (2019).

The main functions are Knet and Knetinhom. These are counterparts of the functions linearK and linearKinhom in the spatstat.linnet package.

The spatstat.linnet functions linearK and linearKinhom are usable (and slightly faster) for small datasets, but require substantial amounts of memory. For larger datasets, the functions Knet and Knetinhom are much more efficient.

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Author(s)

Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>)

Maintainer: Adrian Baddeley <[e-mail]>

References

Rakshit, S., Baddeley, A. and Nair, G. (2019) Efficient code for second order analysis of events on a linear network. Journal of Statistical Software 90 (1) 1–37. DOI: 10.18637/jss.v090.i01

spatstat.Knet documentation built on Nov. 13, 2022, 9:06 a.m.