spotOptimLHS

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Description

This function is an interface to Latin Hypercube Sampling (LHS) fashioned like the optim function. That means, LHS is performed to optimize a target function, i.e. returning the sample with the lowest function value.

Usage

1
spotOptimLHS(par, fn, gr = NULL, lower, upper, control, ...)

Arguments

par

is a point (vector) in the decision space of fn. Points in par will be added to the design created by LHS.

fn

is the target function of type y = f(x, ...)

gr

gradient function, gr is not used (yet)

lower

is a vector that defines the lower boundary of search space

upper

is a vector that defines the upper boundary of search space

control

is a list of additional settings. See details.

...

additional parameters to be passed on to fn

Details

The control list contains:
fevals number of design points created
retries number of designs created during creation of a well spread design
vectorized whether or not fn can evaluate multiple points at once , defaults to FALSE

Value

This function returns a list with:
par parameters of the found solutions, e.g. the Pareto set
value target function values of the found solutions, e.g. the Pareto front
counts number of evaluations of fn

See Also

spotOptimizationInterface spotOptim

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