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shannon
2007 Apr 20
1
Estimating a Normal Mixture Distribution
...,"s1","u2","s2"), function(x,p,u1,s1,u2,s2) NULL)
mix.gr<-function(p,x){
p<-p[1]
u1<-p[2]
s1<-p[3]
u2<-p[4]
s2<-p[5]
colSums(attr(lmix2a(x,p,u1,s1,u2,s2),"gradient"))}
# finally, the optimization using the Broyden-Fletcher-Goldfarb-
Shanno method.
resultsBFGS_D=optim
(p0,mix.obj,mix.gr,x=waiting,method="BFGS",control=list(parscale=c
(0.1,rep(1,4))))
resultsBFGS_D$par
CODE END
The output is given as:
p u1 s1
u2 s2
0.361204 50.000000 5.000000 80.000000 5.000...