View source: R/reverse_survival_clean.R
FertRevSurv | R Documentation |
Reverse Survival Fertility Estimation
FertRevSurv(
ages1_c = 0:14,
popx1_c,
ages5_w = seq(10, 65, 5),
popx5_w,
lx1_c,
lx5_w,
asfr = c(0, 0.017, 0.055, 0.057, 0.041, 0.022, 0.007, 0.002),
asfr_15prior = NULL,
q0_5 = NULL,
q15_45f = NULL,
date_ref
)
ages1_c |
children single ages vector (default 0:14) |
popx1_c |
children population in single ages (x1) matching ages1_c vector |
ages5_w |
women five-year age group ages vector ( default seq( 10, 65, 5 ) ) |
popx5_w |
women population in five-year age group format (x5) matching ages_w vector |
lx1_c |
children survival function vector in single age groups from 0 to 15 |
lx5_w |
women survival function vector in five-year age groups matching ages_w vector |
asfr |
age specific fertility rates for five-year age groups from 10-45 for current period of estimation |
asfr_15prior |
standardized age specific fertility rates for five-year age groups from 10-45 for the period of 15 years before the current inquiry period |
q0_5 |
3 element vector for mortality probability between ages 0-4 for the period of estimation, period 5 years prior to estimation period, and period 10 years prior to estimation period |
q15_45f |
female adult mortality probability for the period of estimation, period 5 years prior to estimation period, and period 10 years prior to estimation period |
date_ref |
reference date of inquiry given in the following formats: Y-m-d (4 digit year - 2 digit month - 2 digit day), Y-m (4 digit year - 2 digit month), Y (4 digit year) |
data.frame with 3 elements: 'year' - reference period of fertility estimation in decimal format; 'TFR' - estimated total fertility rate; 'births' - estimated total number of births
Moultrie TA, RE Dorrington, AG Hill, K Hill, IM Timæus and B Zaba (eds). 2013. Tools for Demographic Estimation. Paris: International Union for the Scientific Study of Population. demographicestimation.iussp.org
# 1 - User input data
popx1_c <- c( 281260, 261320, 268410, 286810, 278990, 293760,
293490, 302060, 315970, 267190, 326980, 280260,
354120, 356920, 354830 )
popx5_w <- c( 815930, 780320, 697160, 626430, 361650, 435880,
393760, 352520, 294280, 230200, 160590, NA )
lx1_c <- c( 1.0000, 0.9320, 0.9275, 0.9228, 0.9165, 0.9125, 0.9110,
0.9094, 0.9079, 0.9063, 0.9048, 0.9032, 0.9017, 0.9001,
0.8986, 0.8970 )
lx5_w <- c( 0.91381, 0.90989, 0.90492, 0.89798, 0.88893, 0.87596,
0.86029, 0.84188, 0.81791, 0.78472, 0.73735, 0.67316 )
q0_5 <- c( 0.0683, 0.1008, 0.1189)
q15_45f <- c( 0.1946, 0.2290, 0.2674 )
asfr <- c( 0.0000, 0.0418,0.1535, 0.1482, 0.1118, 0.0708,
0.0301, 0.0032 )
asfr_15prior <- c( 0.0000, 0.0533, 0.1974, 0.2144, 0.1836, 0.1332,
0.0676, 0.0134 )
FertRevSurv( ages1_c = 0:14, popx1_c = popx1_c,
ages5_w = seq( 10, 65, 5 ), popx5_w = popx5_w,
lx1_c = lx1_c, lx5_w = lx5_w,
asfr = asfr,
asfr_15prior = asfr_15prior,
q0_5 = q0_5, q15_45f = q15_45f,
date_ref = '2008-03-03' )
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