whv_hype: Approximation of the (weighted) hypervolume by Monte-Carlo...

Description Usage Arguments Details Value References See Also Examples

View source: R/whv.R

Description

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.

Usage

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whv_hype(
  data,
  reference,
  ideal,
  maximise = FALSE,
  dist = list(type = "uniform"),
  nsamples = 100000L
)

Arguments

data

(matrix | data.frame)
Matrix or data frame of numerical values, where each row gives the coordinates of a point.

reference

(numeric())
Reference point as a vector of numerical values.

ideal

(numeric())
Ideal point as a vector of numerical values.

maximise

(logical() | logical(1))
Whether the objectives must be maximised instead of minimised. Either a single logical value that applies to all objectives or a vector of logical values, with one value per objective.

dist

(list()) weight distribution. See Details.

nsamples

(integer(1)) number of samples for Monte-Carlo sampling.

Details

A weight distribution \citepAugBadBroZit2009gecco can be provided via the dist argument. The ones currently supported are:

Value

A single numerical value.

References

\insertAllCited

See Also

read_datasets(), eafdiff(), whv_rect()

Examples

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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)))

eaf documentation built on May 7, 2021, 5:06 p.m.