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Accelerate stunting by picking the best results between business as usual, halt downwards trend, and AROC of -50% change between 2012 and 2030.

Usage

accelerate_stunting(
  df,
  ind_ids = billion_ind_codes("hpop"),
  scenario_col = "scenario",
  default_scenario = "default",
  bau_scenario = "historical",
  scenario_name = "acceleration",
  ...
)

Arguments

df

Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.

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().

scenario_col

Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.

default_scenario

name of the default scenario.

bau_scenario

name of scenario to be used for business as usual. Default is historical.

scenario_name

name of scenario

...

additional parameters to be passed to scenario function

Details

Runs:

  • scenario_bau(df, small_is_best = TRUE,...),

  • scenario_aroc(df, aroc_type = "percent_change", percent_change = -50, baseline_year = 2012, target_year = 2030, small_is_best = TRUE, ...)

  • scenario_halt_rise(df, small_is_best = TRUE,...)

Then picks the best result between the three scenarios.