piridge.zeroes

prop

Sigma1

Sigma2

alphamin

alphamax

interval between alpha-values where to look for extrema.

By use of the Pi-function in Ray and Lindsay, 2005, locations of 
  two-component Gaussian mixture density extrema or saddlepoints are computed.

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.

Christian Hennig

Flexible procedures for clustering

piridge.zeroes function

Extrema of two-component Gaussian mixture

piridge.zeroes: Extrema of two-component Gaussian mixture

Description

Usage

Arguments

Value

References

Examples