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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)
proportion of mixture component 1.
mean vector of component 1.
mean vector of component 2.
covariance matrix of component 1.
covariance matrix of component 2.
minimum alpha value.
maximum alpha value.
interval between alpha-values where to look for extrema.
list with components
number of zeroes of Pi-function, i.e., extrema or saddlepoints of density.
estimated alpha-values at which extrema or saddlepoints occur.
alpha
Ray, S. and Lindsay, B. G. (2005) The Topography of Multivariate Normal Mixtures, Annals of Statistics, 33, 2042-2065.
# NOT RUN { q <- piridge.zeroes(0.2,c(1,1),c(2,5),diag(2),diag(2),by=0.1) # }
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