RSD (version 0.2.0)

afsd.test: Compares prospects based on AFSD

Description

It compares two prospects using AFSD criteria, that is the prospect having the minimum violation area from a classic FSD.

Usage

afsd.test(sd.obj)

Value

A list, including all the calculation details.

Arguments

sd.obj

StochasticDominance object.

Details

The returned list has six elements: `winner` indicates the dominant prospect index. It will be zero if neither dominates the other. `epsilon` is the ratio of violated area to the total area between the CDFs. `area` is a vector, where the values show the area between the CDFs correspond to each segment. `total.area` is the total area between the CDFs. `positive.area` is the amount of area where the `area` vector is positive, meaning the `cdf1` is larger than `cdf2`. `negative.area` is like `positive.area` for negative values.

If neither distribution dominates the other by AFSD, the `winner` output will be zero, and it happens only when the expected value of distributions are equal.

The `epsilon` and `winner` output parameters are the ones that should be taken most. The others are the calculation details and are provided for further investigation. A lower the `epsilon`, lower the violation ratio of the dominant distribution, lower the eliminated extreme utilities, higher the number of decision-makers who agree on the dominant distribution.

See Also

[area.btwn.cdfs.calc()] for area calculations.

Examples

sd = createStochasticDominance(outcome1 = c(1,4,7),
                               outcome2 = c(2,3,5),
                               prob1 = c(1/3,1/3,1/3),
                               prob2 = c(1/6,1/6,2/3))
afsd.test(sd)