R/data_popReconstruct.R
burkina_faso.RdExample data and initial estimates for reconstructing the female population in Burkina Faso from 1960 to 2005.
burkina_faso_data
burkina_faso_initial_estimatesburkina_faso_data: [data.table()] with 'population' data.
population: [data.table()] year-sex-age-specific census counts in
years after the baseline year (1975, 1985, 1995, 2005). Age groups are
five-year age groups from 0 to 80+.
burkina_faso_initial_estimates: list of [data.table()] of initial
estimates for each ccmpp() input. Calendar year intervals are for five-year
intervals between 1960 and 2005. Age groups are five-year age groups from 0
to 80+ (except 'survival' goes up to 85+). See Section: Inputs for more
information on each of the inputs.
An object of class list of length 5.
srb: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
value_col: [numeric()] sex-ratio at birth estimates, must be
greater than zero.
asfr: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages_asfr' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] annual age-specific fertility rate
estimates, must be greater than zero.
baseline: [data.table()]
year: [integer()] mid-year for population estimate.
Corresponds to 'years' setting.
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] baseline year population count estimates,
must be greater than zero.
survival: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages_mortality' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] survivorship ratio estimates, must be
greater than zero and less than one.
mx: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages_mortality' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] mortality rate estimates, must be greater
than zero.
ax: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages_mortality' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] average years lived by those dying in the
interval estimates, must be greater than zero and less than the age
interval length.
qx: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages_mortality' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] probability of death estimates, must be
greater than zero and less than one.
net_migration: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] annual net-migration proportion estimates.
immigration: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] annual immigration proportion estimates,
must be greater than zero.
emigration: [data.table()]
year_start: [integer()] start of the calendar year interval
(inclusive). Corresponds to 'years' setting.
year_end: [integer()] end of the calendar year interval (exclusive).
sex: [character()] either 'female' or 'male'. Corresponds to 'sexes'
setting.
age_start: [integer()] start of the age group (inclusive).
Corresponds to 'ages' setting.
age_end: [integer()] end of the age group (exclusive).
value_col: [numeric()] annual emigration proportion estimates, must
be greater than zero.
Wheldon, Mark C., Adrian E. Raftery, Samuel J. Clark, and Patrick Gerland. 2013. “Reconstructing Past Populations With Uncertainty From Fragmentary Data.” Journal of the American Statistical Association 108 (501): 96–110. https://doi.org/10.1080/01621459.2012.737729.