View source: R/accelerate_hpop.R
accelerate_wasting | R Documentation |
Accelerate wasting by picking the best results between halt downwards trend
from start_year
, and AROC by 3% by 2030.
accelerate_wasting(
df,
ind_ids = billion_ind_codes("hpop"),
end_year = 2025,
start_year = 2018,
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
|
end_year |
End year for scenario, defaults to 2025 |
start_year |
Start year for scenario, defaults to 2018. |
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_halt_rise(df, small_is_best = TRUE,...)
scenario_aroc(df, aroc_type = "target", target_value = 3, target_year = 2030, small_is_best = TRUE,...)
Then picks the best result between the two 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_stunting()
,
accelerate_suicide()
,
accelerate_transfats()
,
accelerate_water_rural()
,
accelerate_water_urban()
,
accelerate_water()
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