Initial values for the parameters of a mixture of Gaussians are provided by applying the following steps : 1) clustering the sample into as many clusters as there are mixture components 2) the initial means and standard deviations of each component are taken as the cluster centers and median absolute deviation respectively computed on each component
1  gaussmixt.init(m, x, iter.max = 20, nstart = 10)

m 
number of mixture components 
x 
data sample from which the initial parameters are computed 
iter.max 
maximum number of iteration for kmeans clustering,
default is 20, see 
nstart 
number of random cluster centers chosen (default is 10), see

a matrix of dimension 3 x m
which stores the 3 parameters (pi,
mu, sigma) of each of the m
components.
Julie Carreau
McLachlan, G. and Peel, D. (2000), Finite Mixture Models, Wiley series in probability and statistics
kmeans
,hparetomixt.init
1 2 3  r < rfrechet(500,loc=5,scale=5,shape=10)
m < 2
param.init < gaussmixt.init(2,r)

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