R/data_popReconstruct.R
thailand.RdExample data and initial estimates for reconstructing the female and male population in Thailand from 1960 to 2000.
thailand_data
thailand_initial_estimatesthailand_data: [data.table()] with 'population' data.
population: [data.table()] year-sex-age-specific census counts in
years after the baseline year (1970, 1980, 1990, 2000). Age groups are
five-year age groups from 0 to 80+.
thailand_initial_estimates: list of [data.table()] of initial
estimates for each ccmpp() input. Calendar year intervals are for five-year
intervals between 1960 and 2000. 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. 2015. “Bayesian Reconstruction of Two-Sex Populations by Age: Estimating Sex Ratios at Birth and Sex Ratios of Mortality.” Journal of the Royal Statistical Society. Series A: Statistics in Society 178 (4): 977–1007. https://doi.org/10.1111/rssa.12104.