Accelerate fp by dividing the countries into two groups:
For BRN, CYP, FSM, ISL, LUX, and SYC, return business as usual.
For all other countries, take the best of business as usual and the quantile target for quantile_year = 2018 and 5 quantiles (capped by the maximum regional value in 2018).
Usage
accelerate_fp(
df,
ind_ids = billion_ind_codes("uhc"),
scenario_col = "scenario",
value_col = "value",
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.
- value_col
Name of the column containing indicator value in
df
.- 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
See also
UHC acceleration scenarios
accelerate_anc4()
,
accelerate_art()
,
accelerate_beds()
,
accelerate_bp()
,
accelerate_doctors()
,
accelerate_dtp3()
,
accelerate_fh()
,
accelerate_fpg()
,
accelerate_hwf()
,
accelerate_itn()
,
accelerate_nurses()
,
accelerate_pneumo()
,
accelerate_tb()
,
accelerate_uhc_sanitation()
,
accelerate_uhc_tobacco()