Example data and initial estimates for reconstructing the female population in Burkina Faso from 1960 to 2005.

burkina_faso_data

burkina_faso_initial_estimates

Format

burkina_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.

Inputs

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.

References

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.

popReconstruct R Package

See also