popRecon.ccmp.female: Female Dominant Cohort Component Projection
In popReconstruct: Reconstruct Human Populations of the Recent Past

Description Usage Arguments Details Value Vignettes Author(s) References See Also Examples

View source: R/pop_reconstruction_functions.R

Implements the deterministic female dominant cohort component method of population projection.

1 2	popRecon.ccmp.female(pop, surv, fert, srb = 1.05, mig, proj.steps, age.int = 5, label.dims = FALSE, base.year = "1960")

`pop`	Population count at baseline.
`surv`	Survivorship probabilities: the probability of reaching the age at the start of the interval.
`fert`	Matrix of average annual, single-year age-specific fertility rates (see Details).
`srb`	Sex ratio at birth matrix
`mig`	Net number of migrants as a proportion of prev time period's population.
`proj.steps`	Number of time periods to project forward. If missing, set to ncol(fert).
`age.int`	Width of the age intervals; needed for correct interpretation of survival probabilities and fertility rates.
`label.dims`	Should row and column names be set? Aesthetic.
`base.year`	Baseline year for popualtion projections (aesthetic).

The first row of surv should be nL0/(n*l0), where nL0 and l0 are the usual life table parameters. The last row is survival for age.int years in the open interval.

The elements of the fert argument should not be multiplied by age.int. In other words, the average annual total fertility rates (TFRs) corresponding to the columns of fert are age.int * colSums(fert).

The elements of mig give the average annual net number of migrants, as proportion of the size of the same age-group in the receiving population. Thus, the total net number of migrants to the population over the period

A matrix of projected population counts, age groups as rows, time periods as columns.

burkina-faso-females

Mark C. Wheldon

Preston, S. H., Heuveline, P. and Guillot, M. (2001) Demography, chapter 6. Malden, MA: Blackwell.

make.leslie.matrix, net.number.migrants

data(burkina_faso_females)

(pop.input.mat <-
    popRecon.ccmp.female(pop=burkina.faso.females$baseline.pop.counts
                      ,surv=burkina.faso.females$survival.proportions
                      ,fert=burkina.faso.females$fertility.rates
                      ,mig=burkina.faso.females$migration.proportions
                      ))