osc: Orthodromic Spatial Clustering

Allows distance based spatial clustering of georeferenced data by implementing the City Clustering Algorithm - CCA. Multiple versions allow clustering for matrix, raster and single coordinates on a plain (euclidean distance) or on a sphere (great-circle or orthodromic distance).

Install the latest version of this package by entering the following in R:
install.packages("osc")
AuthorSteffen Kriewald, Till Fluschnik, Dominik Reusser, Diego Rybski
Date of publication2016-05-10 19:05:05
MaintainerSteffen Kriewald <kriewald@pik-potsdam.de>
LicenseGPL
Version1.0.0

View on CRAN

Files

inst
inst/doc
inst/doc/paper.rnw
inst/doc/paper.pdf
inst/doc/paper.R
tests
tests/testthat.R
tests/testthat
tests/testthat/test_cca_single.R tests/testthat/test_coordinate_list.R tests/testthat/test_cca_multi.R
src
src/cca-core.c
src/ccaRevolution.c
NAMESPACE
data
data/exampledata.rda
data/landcover.rda
data/population.rda
data/datalist
R
R/cca.single.R R/cca.R R/getPart.R R/code_revised_cca.R
vignettes
vignettes/paper.rnw
vignettes/pics
vignettes/pics/fig-concordance.tex
vignettes/pics/landcover.pdf
vignettes/pics/exdat1.pdf
vignettes/pics/exdat2.pdf
vignettes/pics/raster.pdf
vignettes/compare.pdf
MD5
build
build/vignette.rds
DESCRIPTION
man
man/assign.data.Rd man/cca.Rd man/landcover.Rd man/coordinate.list.Rd man/population.Rd man/osc.buffer.Rd man/exampledata.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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