Define a function to be passed to the fn_values argument of calibrate_model().

define_calibration_fn(
  type,
  strategy_names,
  element_names,
  cycles,
  groups = NULL,
  aggreg_fn = sum
)

Arguments

type

Type of model values (count or value).

strategy_names

Names of strategies.

element_names

Names of states (for counts) or of state values (for values).

cycles

Cycles of interest.

groups

Optional grouping of values (values in a same group have the same groups).

aggreg_fn

A function to aggregate values in a same group.

Value

A numeric vector.

Examples

example("run_model")
#> #> rn_mdl> # running a single model #> rn_mdl> #> rn_mdl> mod1 <- #> rn_mdl+ define_strategy( #> rn_mdl+ transition = define_transition( #> rn_mdl+ .5, .5, #> rn_mdl+ .1, .9 #> rn_mdl+ ), #> rn_mdl+ define_state( #> rn_mdl+ cost = 543, #> rn_mdl+ ly = 1 #> rn_mdl+ ), #> rn_mdl+ define_state( #> rn_mdl+ cost = 432, #> rn_mdl+ ly = 1 #> rn_mdl+ ) #> rn_mdl+ )
#> No named state -> generating names.
#> No named state -> generating names.
#> #> rn_mdl> res <- run_model( #> rn_mdl+ mod1, #> rn_mdl+ init = c(100, 0), #> rn_mdl+ cycles = 2, #> rn_mdl+ cost = cost, #> rn_mdl+ effect = ly #> rn_mdl+ )
#> No named model -> generating names.
#> #> rn_mdl> # running several models #> rn_mdl> mod2 <- #> rn_mdl+ define_strategy( #> rn_mdl+ transition = define_transition( #> rn_mdl+ .5, .5, #> rn_mdl+ .1, .9 #> rn_mdl+ ), #> rn_mdl+ define_state( #> rn_mdl+ cost = 789, #> rn_mdl+ ly = 1 #> rn_mdl+ ), #> rn_mdl+ define_state( #> rn_mdl+ cost = 456, #> rn_mdl+ ly = 1 #> rn_mdl+ ) #> rn_mdl+ #> rn_mdl+ )
#> No named state -> generating names.
#> No named state -> generating names.
#> #> rn_mdl> res2 <- run_model( #> rn_mdl+ mod1, mod2, #> rn_mdl+ init = c(100, 0), #> rn_mdl+ cycles = 10, #> rn_mdl+ cost = cost, #> rn_mdl+ effect = ly #> rn_mdl+ )
#> No named model -> generating names.
f <- define_calibration_fn( type = c("count", "count", "value"), strategy_names = c("I", "I", "II"), element_names = c("A", "B", "ly"), cycles = c(3, 5, 9), groups = c(1, 1, 2), aggreg_fn = mean )