confusion

matrix of posterior probabilities for observations (rows) to
    belong to mixture components (columns), so entries need to sum up to
    1 for each row.

vector of component proportions, need to sum up to 1.

logical. If <code>TRUE</code>, probabilities are
    initially standardised so that those for components <code>i</code> and
    <code>j</code> add up to one (i.e., if they were the only components).

adjustprobs

Estimates a misclassification probability in a mixture distribution
   between two mixture components from estimated posterior probabilities
   regardless of component parameters, see Hennig (2010).

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.

confusion: Misclassification probabilities in mixtures

Description

Usage

Arguments

Value

References

Examples