Packaged: Thu Sep  7 20:05:06 2006; hornik

Packaged: Sun Sep 10 21:32:11 2006; hornik

Packaged: Wed Oct  4 10:35:44 2006; hornik

Packaged: Sun Oct 29 10:46:12 2006; hornik

Title:		Clustering Method Based on Local Shrinking
Description:	The package contains functions for automatically estimating
the number of clusters and geting the final cluster partition
without any input parameter except the stopping rule for
convergence. The package also provides functions to evaluate
and compare the performances of partitions of a data set
Packaged: Thu Feb 12 11:12:09 2009; stwxq

Packaged: Sun Feb 15 17:23:38 2009; stwxq

Title: Clustering Method Based on Local Shrinking
Author: Fang Chang <changf@mathstat.yorku.ca>, Vincent Carey
Description: The package contains functions for automatically
estimating the number of clusters and geting the final cluster
partition without any input parameter except the stopping rule
for convergence. The package also provides functions to
evaluate and compare the performances of partitions of a data
Packaged: Tue Mar 17 08:39:07 2009; stwxq

estimating the number of clusters and getting the final cluster

Description: We developed the clues R package to provide functions
for automatically estimating the number of clusters and
getting the final cluster partition without any input
parameter except the stopping rule for convergence.

Authors@R: c(person("Fang", "Chang", role=c("aut", "ctb"),
person("Vincent", "Carey", role = c("aut", "ctb"),
person("Ruben H.", "Zamar", role = c("aut", "ctb"),
person("Ross", "Lazarus", role = c("aut", "ctb"),
Depends: R (>= 3.1.0), stats, utils, graphics

X-CRAN-Comment: Orphaned and corrected on 2019-12-03 as Fortran errors
Type mismatch shown by both LTO and gfortran 10.

Title: Monitor Changes in Cluster Solutions of Dynamic Datasets
Description: Monitor and trace changes in clustering solutions of accumulating datasets
at successive time points. The clusters can adopt External and Internal transition at
succeeding time points. The External transitions comprise of Survived, Merged, Split,
Disappeared, and newly Emerged candidates. In contrast, Internal transition includes changes
in location and cohesion of the survived clusters. The package uses MONIC framework developed by
Spiliopoulou, Ntoutsi, Theodoridis, and Schult (2006)<doi:10.1145/1150402.1150491> .
Depends: R (>= 3.5), flexclust, methods, graphics