piridge: Ridgeline Pi-function

In fpc: Flexible Procedures for Clustering

Ridgeline Pi-function

Description

The Pi-function is given in (6) in Ray and Lindsay, 2005. Equating it to the mixture proportion yields locations of two-component Gaussian mixture density extrema.

Usage

piridge(alpha, mu1, mu2, Sigma1, Sigma2, showplot=FALSE)

Arguments

alpha	sequence of values between 0 and 1 for which the Pi-function is computed.
mu1	mean vector of component 1.
mu2	mean vector of component 2.
Sigma1	covariance matrix of component 1.
Sigma2	covariance matrix of component 2.
showplot	logical. If TRUE, the Pi-function is plotted against alpha.

Value

Vector of values of the Pi-function for values of alpha.

Author(s)

Christian Hennig [e-mail] https://www.unibo.it/sitoweb/christian.hennig/en/

References

Ray, S. and Lindsay, B. G. (2005) The Topography of Multivariate Normal Mixtures, Annals of Statistics, 33, 2042-2065.

Examples

  q <- piridge(seq(0,1,0.1),c(1,1),c(2,5),diag(2),diag(2))

fpc documentation built on Sept. 24, 2024, 9:07 a.m.