View source: R/accelerate_hpop.R
| accelerate_stunting | R Documentation | 
Accelerate stunting by picking the best results between business as usual, halt downwards trend, and AROC of -50% change between 2012 and 2030.
accelerate_stunting(
  df,
  ind_ids = billion_ind_codes("hpop"),
  scenario_col = "scenario",
  default_scenario = "default",
  bau_scenario = "historical",
  scenario_name = "acceleration",
  ...
)
| 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
 | 
| 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  | 
| scenario_name | name of scenario | 
| ... | additional parameters to be passed to scenario function | 
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.
HPOP acceleration scenarios
accelerate_adult_obese(),
accelerate_alcohol(),
accelerate_child_obese(),
accelerate_child_viol(),
accelerate_devontrack(),
accelerate_fuel(),
accelerate_hpop_sanitation_rural(),
accelerate_hpop_sanitation_urban(),
accelerate_hpop_sanitation(),
accelerate_hpop_tobacco(),
accelerate_ipv(),
accelerate_overweight(),
accelerate_pm25(),
accelerate_road(),
accelerate_suicide(),
accelerate_transfats(),
accelerate_wasting(),
accelerate_water_rural(),
accelerate_water_urban(),
accelerate_water()
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