mixdens

an mclust model name.
    See <code><a href="/link/mclustModelNames?package=fpc&version=2.1-6&to=mclust" rd-options="mclust" data-mini-rdoc="mclust::mclustModelNames">mclustModelNames</a></code>.

modelName

data matrix; density values are computed for every
    observation (row).

data

parameters of Gaussian mixture in the format used in
    the output of <code><a href="/link/summary.mclustBIC?package=fpc&version=2.1-6&to=mclust" rd-options="mclust" data-mini-rdoc="mclust::summary.mclustBIC">summary.mclustBIC</a></code>.

parameters

Computes density values for data from a mixture of multivariate Gaussian
  distributions with parameters based on the way models are specified
  and parameters are stored in package mclust.

multivariate

cluster

Various methods for clustering and cluster validation.
  Fixed point clustering. Linear regression clustering. Clustering by 
  merging Gaussian mixture components. Symmetric 
  and asymmetric discriminant projections for visualisation of the 
  separation of groupings. Cluster validation statistics
  for distance based clustering including corrected Rand index. 
  Cluster-wise cluster stability assessment. Methods for estimation of 
  the number of clusters: Calinski-Harabasz, Tibshirani and Walther's 
  prediction strength, Fang and Wang's bootstrap stability. 
  Gaussian/multinomial mixture fitting for mixed 
  continuous/categorical variables. Variable-wise statistics for cluster
  interpretation. DBSCAN clustering. Interface functions for many 
  clustering methods implemented in R, including estimating the number of
  clusters with kmeans, pam and clara. Modality diagnosis for Gaussian
  mixtures. For an overview see package?fpc.

mixdens: Density of multivariate Gaussian mixture, mclust parameterisation

Description

Usage

Arguments

Value

Examples