Data to plot linear partial value function

Generate data used to plot a linear partial value function for a particular criteria given model outcomes.

lpvf_plot_data(x, criteria_min = NULL, criteria_max = NULL,
  optimal = c("low", "high"), length_out = 1000)

Arguments

x	Model outcomes for a particular criteria on the original scale.
criteria_min	A vector of minimum values for each criterion. If NULL, then the minimum value is computed automatically.
criteria_max	A vector of maximum values for each criterion. If NULL, then the maximum value is computed automatically.
optimal	If "low", then lower values of the outcome are better, and, if "high", then higher values of the outcome are better.
length_out	Number of points between minimum and maximum values of x.

Value

A data.table containing x and y coordinates for a line plot.

See also

mcda

Examples

outcome <- rnorm(10, mean = 100, sd = 11)

# Using optimal
plot_data <- lpvf_plot_data(outcome, optimal = "high")
print(plot_data)
#>               x           y
#>    1:  83.84492   0.0000000
#>    2:  83.88159   0.1001001
#>    3:  83.91825   0.2002002
#>    4:  83.95492   0.3003003
#>    5:  83.99158   0.4004004
#>   ---                      
#>  996: 120.32584  99.5995996
#>  997: 120.36250  99.6996997
#>  998: 120.39917  99.7997998
#>  999: 120.43583  99.8998999
#> 1000: 120.47249 100.0000000

# Using criteria_min and criteria_max
plot_data <- lpvf_plot_data(outcome, criteria_min = 80, criteria_max = 130)
print(plot_data)
#>               x           y
#>    1:  80.00000   0.0000000
#>    2:  80.05005   0.1001001
#>    3:  80.10010   0.2002002
#>    4:  80.15015   0.3003003
#>    5:  80.20020   0.4004004
#>   ---                      
#>  996: 129.79980  99.5995996
#>  997: 129.84985  99.6996997
#>  998: 129.89990  99.7997998
#>  999: 129.94995  99.8998999
#> 1000: 130.00000 100.0000000