Description: Perform a correlational class analysis of the data, resulting in a partition of the data into separate modules.

Packaged: 2013-12-10 07:04:09 UTC; ElectricShhh

Title: Generate correlated count random variables
Description: Generate high-dimensional correlated count random variables with a prespecified Pearson correlation.
Packaged: Sat Nov  8 21:26:42 2008; erhardt

Packaged: Mon Nov 10 10:58:16 2008; erhardt

Packaged: Thu Nov 27 15:00:29 2008; erhardt

Description: Generate high-dimensional correlated count random
variables with a prespecified Pearson correlation.
Packaged: Fri Oct 9 09:36:04 2009; erhardt

Packaged: Fri Nov 13 11:12:59 2009; erhardt

Title: Community Estimation in G-Models via CORD
Author: Xi (Rossi) LUO, Florentina Bunea, Christophe Giraud
Description: Partition data points (variables) into communities/clusters, similar to clustering algorithms, such as k-means and hierarchical clustering.  This package implements a clustering algorithm based on a new metric CORD, defined for high dimensional parametric or semi-parametric distributions.  Read http://arxiv.org/abs/1508.01939 for more details.

Title: Calculation of the OPTICS Cordillera
Authors@R: c(person(given="Thomas", family="Rusch", email="thomas.rusch@wu.ac.at", role = c("aut","cre")), person(given="Patrick",family="Mair", role = "ctb"),person(given="Kurt",family="Hornik", role = "ctb"))
Author: Thomas Rusch [aut, cre], Patrick Mair [ctb], Kurt Hornik [ctb]
Description: Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera measures the amount of 'clusteredness' in a numeric data matrix within a distance-density based framework for a given minimum number of points comprising a cluster, as described in Rusch, Hornik, Mair (2017) <doi:10.1080/10618600.2017.1349664>. There is an R native version and a version that uses 'ELKI', with methods for printing, summarizing, and plotting the result. There also is an interface to the reference implementation of OPTICS in 'ELKI'.
SystemRequirements: ELKI (>=0.6.0 if used)