Description Usage Arguments Details Value References See Also Examples
Return an estimation of the hypervolume of the space dominated by the input data following the procedure described by \citetAugBadBroZit2009gecco. A weight distribution describing user preferences may be specified.
1 2 3 4 5 6 7 8 
data 
( 
reference 
( 
ideal 
( 
maximise 
( 
dist 
( 
nsamples 
( 
A weight distribution \citepAugBadBroZit2009gecco can be provided via the dist
argument. The ones currently supported are:
type="point"
describes a goal in the objective space, where mu
gives the coordinates of the goal. The resulting weight distribution is a multivariate normal distribution centred at the goal.
type="exponential"
describes an exponential distribution with rate parameter 1/mu
, i.e., λ = \frac{1}{μ}.
A single numerical value.
read_datasets()
, eafdiff()
, whv_rect()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1)
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1)
whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1,
dist = list(type="exponential", mu=0.2))
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1,
dist = list(type="exponential", mu=0.2))
whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1,
dist = list(type="point", mu=c(1,1)))
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1,
dist = list(type="point", mu=c(1,1)))

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