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)))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.