The purpose of the mapping function is to transform a weights vector that does not meet all the constraints into a weights vector that does meet the constraints, if one exists, hopefully with a minimum of transformation.
fn_map(weights, portfolio, relax = FALSE, verbose = FALSE, ...)vector of weights
object of class portfolio
TRUE/FALSE, default FALSE. Enable constraints to be relaxed.
print error messages for debuggin purposes
any other passthru parameters
weights: vector of transformed weights meeting constraints.
min: vector of min box constraints that may have been modified if relax=TRUE.
max: vector of max box constraints that may have been modified if relax=TRUE.
cLO: vector of lower bound group constraints that may have been modified if relax=TRUE.
cUP: vector of upper bound group constraints that may have been modified if relax=TRUE.
The first step is to test for violation of the constraint. If the constraint is violated, we will apply a transformation such that the weights vector satisfies the constraints. The following constraint types are tested in the mapping function: leverage, box, group, and position limit. The transformation logic is based on code from the random portfolio sample method.
If relax=TRUE, we will attempt to relax the constraints if a feasible
portfolio could not be formed with an initial call to rp_transform.
We will attempt to relax the constraints up to 5 times. If we do not have a
feasible portfolio after attempting to relax the constraints, then we will
default to returning the weights vector that violates the constraints.