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Print an object of class "prova_eu" (expected utility)

Source: R/display.R
print.prova_eu.Rd

This base::print() method is a utility to display value and revisability of an "prova_mi" (mutual information) object obtained with mutualinfo().

Usage

# S3 method for class 'prova_eu'
print(x, elements = NULL, digits = TRUE, edigits = 2, ...)

Arguments

x

Object of class "prova_eu" (expected utility), obtained with exputility().

elements

character or integer vector, or NULL (default): elements of the "expected utility" object to display. The syntax is the same as with [. If NULL, the elements 'value', 'value.acc', 'optimal.probs' are displayed together in a special way.

digits

positive integer or NULL or TRUE (default): minimal number of significant digits, see base::print.default(). If value is TRUE, then the significant digits for element 'value' are determined from is respective 'value.acc' (see exputility()), according to the rules of the Guide to the expression of Uncertainty in Measurement, keeping as many digits as given in parameter edigits.

edigits

positive integer, default 2: number of significant digits for element 'value' and 'quantiles', if digits = TRUE.

...

Other parameters to be passed to base::print().

Value

Its x argument, invisibly; see base::print().

References

See also

exputility() to calculate expected utilities and their revisability.

Examples

## Use the example "prova_K" (knowledge) object 'Kexample'
## calculated from the "penguins" dataset;
## variates: 'species' and 'bill_len'

## define a utility matrix with four actions,
## and outcomes depending on the variate 'species'
umatrix <- matrix(c(
 1.80, 0.42, 1.60, -0.12, -1.10, 0.20, -0.51, 0.35, -0.49, 0.35, -0.48, 0.62
 ), nrow = 4, ncol = 3, dimnames = list(actions = paste0('A', 1:4), NULL))

print(umatrix)
#>        
#> actions  [,1]  [,2]  [,3]
#>      A1  1.80 -1.10 -0.49
#>      A2  0.42  0.20  0.35
#>      A3  1.60 -0.51 -0.48
#>      A4 -0.12  0.35  0.62

## Calculate the probability of the 'species outcomes
probs <- Pr(data.frame(species = c('Adelie', 'Chinstrap', 'Gentoo')),
  Kexample)

## Calculate the expected utilities of the actions
eu <- exputility(umatrix, probs)

## Print the expected utility of each action, its numerical accuracy,
## and the probability that it would be optimal if more data were available

print(eu)
#>        
#> actions   EU     +/-    prob.
#>      A1   0.3981 0.0048 0.013
#>      A2   0.3511 0.0013 0.058
#>      A3 * 0.4307 0.0036 0.93 
#>      A4   0.2403 0.0015 0