dMod (version 0.3.1)

+.objfn: Direct sum of objective functions

Description

Direct sum of objective functions

Usage

"+"(x1, x2)

Arguments

x1

function of class objfn

x2

function of class objfn

Value

Object of class objfn.

Details

The objective functions are evaluated and their results as added. Sometimes, the evaluation of an objective function depends on results that have been computed internally in a preceding objective function. Therefore, environments are forwarded and all evaluations take place in the same environment. The first objective function in a sum of functions generates a new environment.

See Also

normL2, constraintL2, priorL2, datapointL2

Examples

## 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))