Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/utility.aggregate.r

Function to perform a harmonic aggregation (weighted harmonic mean) of values or utilities with offset. The offset is added to the arguments and subtracted from the result.

1 |

`u` |
numeric vector of values or utilities to be aggregated. |

`par` |
numeric vector of weights appended by an offset for calculating the
weighted harmonic mean minus an offset of the values provided in the
argument |

The aggregation function is defined by

*u = 1 / ( sum wi/(ui+delta) ) - delta*

where *delta* is the last parameter appended to the weights.

The following figure shows examples of the behaviour of this aggregation function and its special case `utility.aggregate.harmo`

for the two-dimensional case:

The function returns the aggregated value or utility.

Peter Reichert <peter.reichert@eawag.ch>

Short description of the package:

Reichert, P., Schuwirth, N. and Langhans, S.,
Constructing, evaluating and visualizing value and utility functions for decision support, Environmental Modelling & Software 46, 283-291, 2013.

Description of aggregation techniques:

Langhans, S.D., Reichert, P. and Schuwirth, N.,
The method matters: A guide for indicator aggregation in ecological assessments.
Ecological Indicators 45, 494-507, 2014.

Textbooks on the use of utility and value functions in decision analysis:

Keeney, R. L. and Raiffa, H. Decisions with Multiple Objectives - Preferences and Value Tradeoffs. John Wiley & Sons, 1976.

Eisenfuehr, F., Weber, M. and Langer, T., Rational Decision Making, Springer, Berlin, 2010.

Constructor of aggregation node:

`utility.aggregation.create`

Aggregation techniques provided by uncsim:

`utility.aggregate.add`

for additive aggregation (weighted arithmetic mean),

`utility.aggregate.min`

for minimum aggregation,

`utility.aggregate.max`

for maximum aggregation,

`utility.aggregate.geo`

or `utility.aggregate.cobbdouglas`

for geometric or Cobb-Douglas aggregation (weighted geometric mean),

`utility.aggregate.geooff`

for geometric aggregation with offset,

`utility.aggregate.revgeo`

for reverse geometric aggregation,

`utility.aggregate.revgeooff`

for reverse geometric aggregation with offset,

`utility.aggregate.harmo`

for harmonic aggregation (weighted harmonic mean),

`utility.aggregate.harmooff`

for harmonic aggregation with offset,

`utility.aggregate.revharmo`

for reverse harmonic aggregation,

`utility.aggregate.revharmooff`

for reverse harmonic aggregation with offset,

`utility.aggregate.mult`

for multiplicative aggregation,

`utility.aggregate.mix`

for a mixture of additive, minimum, and geometric aggregation,

`utility.aggregate.addmin`

for a mixture of additive and minimum aggregation.

`utility.aggregate.addpower`

for additive power aggregation (weighted power mean),

`utility.aggregate.revaddpower`

for reverse additive power aggregation,

`utility.aggregate.addsplitpower`

for splitted additive power aggregation,

`utility.aggregate.revaddsplitpower`

for reverse splitted additive power aggregation,

`utility.aggregate.bonusmalus`

for an aggregation technique that considers some of the values or utilities of sub-objectives only as bonus or malus.

1 | ```
utility.aggregate.harmooff(c(0.2,0.8), par=c(1,1,0.1))
``` |

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