Solves Teitz and Bart's p-median problem - given a set of points attempts to find subset of size p such that summed distances of any point in the set to the nearest point in p is minimised. Although generally effective, this algorithm does not guarantee that a globally optimal subset is found.

Author | Chris Brunsdon |

Date of publication | 2015-02-13 20:23:02 |

Maintainer | Chris Brunsdon <christopher.brunsdon@nuim.ie> |

License | GPL (>= 2) |

Version | 1.0 |

**allocate:** Teitz-Bart algorithm applied to Spatial* and...

**allocations:** Teitz-Bart algorithm applied to Spatial* and...

**euc.dists:** Euclidean distances from a Spatial* or Spatial*DataFrame...

**mink.dists:** Minkowski distances from a Spatial* or Spatial*DataFrame...

**star.diagram:** Creates the lines for a 'star diagram'

**tb:** Teitz-Bart algorithm applied to Spatial* and...

**tbart-package:** Teitz and Bart's p-median problem with Spatial* and...

**tb.raw:** Teitz-Bart algorithm applied to a 'raw' distance matrix

tbart

tbart/src

tbart/src/Makevars

tbart/src/tb.cpp

tbart/src/Makevars.win

tbart/src/RcppExports.cpp

tbart/NAMESPACE

tbart/R

tbart/R/tbart-describes.R
tbart/R/RcppExports.R
tbart/R/tbmain.R
tbart/MD5

tbart/DESCRIPTION

tbart/man

tbart/man/mink.dists.Rd
tbart/man/euc.dists.Rd
tbart/man/tbart-package.Rd
tbart/man/allocate.Rd
tbart/man/star.diagram.Rd
tbart/man/allocations.Rd
tbart/man/tb.raw.Rd
tbart/man/tb.Rd
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