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## Generate three objective functions
prior <- structure(rep(0, 5), names = letters[1:5])
obj1 <- constraintL2(mu = prior, attr.name = "center")
obj2 <- constraintL2(mu = prior + 1, attr.name = "right")
obj3 <- constraintL2(mu = prior - 1, attr.name = "left")
## Evaluate first objective function on a random vector
pouter <- prior + rnorm(length(prior))
print(obj1(pouter))
## Split into fixed and non-fixed part
fixed <- pouter[4:5]
pouter <- pouter[1:3]
print(obj1(pouter, fixed = fixed))
## Visualize the result by a parameter profile
myfit <- trust(obj1, pouter, rinit = 1, rmax = 10, fixed = fixed)
myprof <- profile(obj1, myfit$argument, "a", fixed = fixed)
plotProfile(myprof)
## Create new objective function by adding the single ones,
## then evalue the random vector again
pouter <- prior + rnorm(length(prior))
obj <- obj1 + obj2 + obj3
print(obj(pouter))
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