fixed_target: Scenario to reach a fixed target
In gpw13/billionaiRe: Calculate the WHO Triple Billions

scenario_fixed_target

R Documentation

Scenario to reach a fixed target

Description

Those scenarios allow to reach a target value from a baseline year by target year.

scenario_fixed_target() provides values for scenarios stated as "Reach XX% in INDICATOR by YEAR" or "Eliminate XX by YEAR".

scenario_fixed_target_col() wraps around scenario_fixed_target to provide targets from a column specified in target_col rather than a single value.

scenario_halt_rise() is a special case of scenario_fixed_target_col() where each country aims at a value of a specific year.

The returned scenario is a portion of the straight line drawn from the baseline_year value to the target_year. Only values for years between start_year and end_year will be returned.

If value_col has values that are higher or lower than the scenario values, then only value_col will be kept, depending on small_is_best. For instance, if the scenario value is 80 and the value 75 and small_is_best is TRUE, then 75 will be kept.

Usage

scenario_fixed_target(
  df,
  target_value,
  value_col = "value",
  scenario_col = "scenario",
  start_year = 2018,
  end_year = 2025,
  baseline_year = start_year,
  target_year = end_year,
  scenario_name = glue::glue("{target_value}_{target_year}"),
  small_is_best = FALSE,
  trim = TRUE,
  keep_better_values = TRUE,
  upper_limit = 100,
  lower_limit = 0,
  trim_years = TRUE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  ind_ids = billion_ind_codes("all"),
  default_scenario = "default"
)

scenario_fixed_target_col(
  df,
  value_col = "value",
  scenario_col = "scenario",
  start_year = 2018,
  end_year = 2025,
  baseline_year = start_year,
  target_col = "target",
  target_year = end_year,
  scenario_name = glue::glue("{target_col}_{target_year}"),
  small_is_best = FALSE,
  trim = TRUE,
  keep_better_values = TRUE,
  upper_limit = 100,
  lower_limit = 0,
  trim_years = TRUE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  ind_ids = billion_ind_codes("all"),
  default_scenario = "default"
)

scenario_halt_rise(
  df,
  value_col = "value",
  start_year = 2018,
  end_year = 2025,
  baseline_year = start_year,
  target_year = end_year,
  scenario_col = "scenario",
  scenario_name = glue::glue("halt_rise"),
  upper_limit = 100,
  lower_limit = 0,
  trim = TRUE,
  keep_better_values = FALSE,
  small_is_best = FALSE,
  trim_years = TRUE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  ind_ids = billion_ind_codes("all"),
  default_scenario = "default"
)

Arguments

`df`	Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
`target_value`	value to be achieved by scenario by `target_year`
`value_col`	Column name of column with indicator values.
`scenario_col`	Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.
`start_year`	Start year for scenario, defaults to 2018.
`end_year`	End year for scenario, defaults to 2025
`baseline_year`	Year from which the scenario is measured. Defaults to `start_year`
`target_year`	Year by which the scenario should eventually be achieved. Defaults to `end_year`
`scenario_name`	Name of the scenario. Defaults to scenario_percent_change_baseline_year
`small_is_best`	Logical to identify if a lower value is better than a higher one (e.g. lower obesity in a positive public health outcome, so obesity rate should have small_is_best = TRUE).
`trim`	logical to indicate if the data should be trimmed between `upper_limit` and `lower_limit`.
`keep_better_values`	logical to indicate if "better" values should be kept from `value_col` if they are present. Follows the direction set in `small_is_best`. For instance, if small_is_best is TRUE, then `value_col` lower than `col` will be kept.
`upper_limit`	limit at which the indicator should be caped. Can take any of "guess", or any numeric. `guess` (default) will take 100 as the limit if `percent_change` is positive, and 0 if negative.
`lower_limit`	limit at which the indicator should be caped. Can take any of "guess", or 0 to 100. `guess` (default) will take 0 as the limit if `percent_change` is positive, and 100 if negative.
`trim_years`	logical to indicate if years before `start_year_trim` and after `end_year_trim` should be removed
`start_year_trim`	(integer) year to start trimming from.
`end_year_trim`	(integer) year to end trimming.
`ind_ids`	Named vector of indicator codes for input indicators to the Billion. Although separate indicator codes can be used than the standard, they must be supplied as a named vector where the names correspond to the output of `billion_ind_codes()`.
`default_scenario`	name of the default scenario to be used.
`target_col`	name of column with targets