hparetomixt.init {condmixt}  R Documentation 
Initial values for the parameters of a mixture of hybrid Paretos are
provided by applying the following steps :
1) clustering the sample into as many clusters as there are mixture
components
2) estimating the hybrid Pareto parameters for each component on the data
from each cluster with the momentlike estimators, see
hpareto.mme
hparetomixt.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 4 x m
which stores the 4 parameters (pi,
xi, mu, sigma) of each of the m
components.
Julie Carreau
Carreau, J. and Bengio, Y. (2009), A Hybrid Pareto Model for Asymmetric Fattailed Data: the Univariate Case, 12, Extremes
r < rfrechet(500,loc=5,scale=5,shape=5)
m < 2
param.init < hparetomixt.init(m,r)