fpc: piridge.zeroes – R documentation

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piridge.zeroes

Extrema of two-component Gaussian mixture

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

piridge.zeroes(prop, mu1, mu2, Sigma1, Sigma2, alphamin=0,
                          alphamax=1,by=0.001)

`prop`	proportion of mixture component 1.
`mu1`	mean vector of component 1.
`mu2`	mean vector of component 2.
`Sigma1`	covariance matrix of component 1.
`Sigma2`	covariance matrix of component 2.
`alphamin`	minimum alpha value.
`alphamax`	maximum alpha value.
`by`	interval between alpha-values where to look for extrema.

list with components

`number.zeroes`	number of zeroes of Pi-function, i.e., extrema or saddlepoints of density.
`estimated.roots`	estimated `alpha`-values at which extrema or saddlepoints occur.

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

q <- piridge.zeroes(0.2,c(1,1),c(2,5),diag(2),diag(2),by=0.1)

Flexible Procedures for Clustering

v2.2-9

GPL

Authors

Christian Hennig <christian.hennig@unibo.it>

Initial release

2020-12-06