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Construct a target grid for prediction

Source: R/helpers.R
create_target.Rd

Builds a target grid, for use with [predict.imugap_fit()], from vectors of locations, ages, cohorts, and doses. This is pure construction and does not reference a fitted model, so it can be called without a fit (e.g. to expand a request into rows before any fit exists). To validate a target against a specific fit – or to canonicalize a target you built yourself as a data.frame – use [canonicalize_target()]; [predict.imugap_fit()] does this for you.

Usage

create_target(
  location,
  age,
  cohort,
  dose,
  mode = c("error", "enumerate", "recycle", "snapshot")
)

Arguments

location

a vector of location IDs to target.

age

vector of ages for which to predict coverage, consistent with [canonicalize_populations()].

cohort

vector of cohorts for which to predict coverage, consistent with [canonicalize_populations()].

dose

vector of doses for which to predict coverage, consistent with [canonicalize_observations()].

mode

one of "error" (default), "enumerate", "recycle", or "snapshot", controlling how the vector inputs combine:

  • "error": all vector inputs must have the same length.

  • "enumerate": all combinations of the inputs.

  • "recycle": recycle the inputs out to the least-common-multiple length.

  • "snapshot": cohort must be a single reference value (the oldest cohort); locations, ages, and doses are enumerated with a cohort for each age such that age + cohort is constant, using the maximum value of age to set that constant (cohort_i = cohort_ref + max(age) - age_i), i.e. a snapshot in time.

Value

a data.table target grid with columns obs_c_id, loc_id, age, cohort, dose, and weight.

See also

[canonicalize_target()], [predict.imugap_fit()]

Examples

# "error" mode: all vector inputs must have the same length.
create_target(
  location = c("Blue Heron School", "Bluebird Learning Center"),
  age = c(1, 2), cohort = c(2, 3), dose = c(1, 1), mode = "error"
)
#>    obs_c_id                   loc_id   age cohort  dose weight
#>       <int>                   <char> <num>  <num> <num>  <num>
#> 1:        1        Blue Heron School     1      2     1      1
#> 2:        2 Bluebird Learning Center     2      3     1      1

# "enumerate": all combinations of the inputs.
create_target(
  location = c("Blue Heron School", "Bluebird Learning Center"),
  age = c(1, 2), cohort = c(2, 3), dose = c(1), mode = "enumerate"
)
#>    obs_c_id                   loc_id   age cohort  dose weight
#>       <int>                   <char> <num>  <num> <num>  <num>
#> 1:        1        Blue Heron School     1      2     1      1
#> 2:        2 Bluebird Learning Center     1      2     1      1
#> 3:        3        Blue Heron School     2      2     1      1
#> 4:        4 Bluebird Learning Center     2      2     1      1
#> 5:        5        Blue Heron School     1      3     1      1
#> 6:        6 Bluebird Learning Center     1      3     1      1
#> 7:        7        Blue Heron School     2      3     1      1
#> 8:        8 Bluebird Learning Center     2      3     1      1

# "snapshot": cohort is a single reference; cohorts are set so age + cohort is
# constant, using max(age).
create_target(
  location = c("Blue Heron School", "Bluebird Learning Center"),
  age = c(1, 2, 3), cohort = 5, dose = c(1), mode = "snapshot"
)
#>    obs_c_id                   loc_id   age cohort  dose weight
#>       <int>                   <char> <num>  <num> <num>  <num>
#> 1:        1        Blue Heron School     1      7     1      1
#> 2:        2 Bluebird Learning Center     1      7     1      1
#> 3:        3        Blue Heron School     2      6     1      1
#> 4:        4 Bluebird Learning Center     2      6     1      1
#> 5:        5        Blue Heron School     3      5     1      1
#> 6:        6 Bluebird Learning Center     3      5     1      1