Create a data frame of gpl loss functions and their parameters

Recycles scalar arguments to length N and builds one gpl loss function per target.

Usage

new_gpl_df(
  N = NULL,
  target_names = NA,
  g = "x",
  dg = NA,
  kappa = 1,
  alpha = 1,
  O = NA,
  U = NA,
  offset = 0
)

Arguments

N

number of targets. If NULL, inferred from the longest argument.

target_names

names of the targets, one per row.

g

a non-decreasing increment function, supplied either as a function or as a string in the variable x such as "log(x)".

dg

derivative of g. Defaults to NA, in which case it is derived symbolically from g when needed.

kappa

scale factor.

alpha

normalized loss when the outcome y exceeds the allocation x. Exactly one of alpha and U must be supplied.

O

cost incurred when the allocation x exceeds the outcome y; equals kappa * (1 - alpha).

U

cost incurred when the outcome y exceeds the allocation x; equals kappa * alpha.

offset

a constant, or a function of y, added to the loss. The default of 0 gives a loss with L(x, x) = 0.

Value

A tibble of class gpl_df with one row per target, columns for each loss parameter, and a gpl_loss_fun list column of loss functions.

Examples

new_gpl_df(N = 3, alpha = c(0.5, 0.7, 0.9), target_names = c("a", "b", "c"))
#> # A tibble: 3 × 9
#>   g     dg    target_names kappa alpha O     U     offset gpl_loss_fun
#> * <chr> <lgl> <chr>        <dbl> <dbl> <lgl> <lgl>  <dbl> <list>      
#> 1 x     NA    a                1   0.5 NA    NA         0 <fn>        
#> 2 x     NA    b                1   0.7 NA    NA         0 <fn>        
#> 3 x     NA    c                1   0.9 NA    NA         0 <fn>